Back
to Bioinformatics
Enhanced by
Neuroinformation
Bioinformatics Reviews: 2003
(82 References)
Adams, P. D., R. W. Grosse-Kunstleve, et al. (2003). "Computational aspects of high-throughput crystallographic macromolecular structure determination." Methods Biochem Anal 44: 75-87.
Aitchison, J. D. and T. Galitski (2003). "Inventories to insights." J Cell Biol 161(3): 465-9.
"In the long course of cell life on this earth it remained, for our age, for our generation, to receive the full ownership of our inheritance. We have entered the cell, the Mansion of our birth and started the inventory of our acquired wealth." (Albert Claude, Nobel lecture, 1974).
Altman, R. B. and J. M. Dugan (2003). "Defining bioinformatics and structural bioinformatics." Methods Biochem Anal 44: 3-14.
Andersen, C. A. and B. Rost (2003). "Secondary structure assignment." Methods Biochem Anal 44: 341-63.
Armitage, J. P., C. J. Dorman, et al. (2003). "Thinking and decision making, bacterial style: Bacterial Neural Networks, Obernai, France, 7th-12th June 2002." Mol Microbiol 47(2): 583-93.
Bacteria exhibit a bewildering range of behavioural responses and permutations of metabolic pathways for maximum exploitation of their environment. These are based on sensory perception of external and internal signals through batteries of surface and cytoplasmic receptors, evaluation of complex information flows and rapid decision making. Appreciation of the diversity of bacterial behaviour and adaptation capacities requires the study of a broad range of organisms and at this meeting we sampled more than 30 species with new findings which included the nature of gaseous receptors, advances in chemotaxis, subversion of host defences by pathogens, adaptation to high salt, community life and its obvious benefits, cell to cell communications and even the nature of bacterial circadian rhythms. With around 80 bacterial genomes now completed, and many more almost there, it was appropriate to complete the meeting with an introduction to Systems Biology and prospects for simulating the virtual cell. The versatility and seemingly 'intelligent' behaviour of bacteria will continue to fascinate, and this meeting on Bacterial Neural Networks fully reflected the excitement of this field.
Arnosti, D. N. (2003). "Analysis and function of transcriptional regulatory elements: insights from Drosophila." Annu Rev Entomol 48: 579-602.
Analysis of gene expression is assuming an increasingly important role in elucidating the molecular basis of insect biology. Transcriptional regulation of gene expression is directed by a variety of cis-acting DNA elements that control spatial and temporal patterns of expression. This review summarizes current knowledge about properties of transcriptional regulatory elements, based largely on research in Drosophila melanogaster, and outlines ways that new technologies are providing tools to facilitate the study of transcriptional regulatory elements in other insects.
Baker, N. A. and J. A. McCammon (2003). "Electrostatic interactions." Methods Biochem Anal 44: 427-40.
Bartlett, G. J., A. E. Todd, et al. (2003). "Inferring protein function from structure." Methods Biochem Anal 44: 387-407.
Bertini, I. and A. Rosato (2003). "Bioinorganic chemistry in the postgenomic era." Proc Natl Acad Sci U S A 100(7): 3601-4.
Genome sequencing has revolutionized all fields of life sciences. Bioinorganic chemistry is certainly not immune to this influence, which is presenting unprecedented challenges. A new goal for bioinorganic chemistry is the investigation of the linkages between inorganic elements and genomic information. This requires new advancements andor the development of new expertise in fields such as bioinformatics and genetics but also provides a driving force to push forward the exploitation of traditional analytical techniques and spectroscopic tools. The "case study" of metal homeostasis in cells is discussed to provide a flavor of the current evolution of the field.
Boguski, M. S. and M. W. McIntosh (2003). "Biomedical informatics for proteomics." Nature 422(6928): 233-7.
Success in proteomics depends upon careful study design and high-quality biological samples. Advanced information technologies, and also an ability to use existing knowledge to the full, will be crucial in making sense of the data. Despite its genome-scale potential, proteome analysis is at a much earlier stage of development than genomics and gene expression (microarray) studies. Fundamental issues involving biological variability, pre-analytic factors and analytical reproducibility remain to be resolved. Consequently, the analysis of proteomics data is currently informal and relies heavily on expert opinion. Databases and software tools developed for the analysis of molecular sequences and microarrays are helpful, but are limited owing to the unique attributes of proteomics data and differing research goals.
Bono, H. and M. C. Nakao (2003). "[Introduction to the practical analysis of DNA microarray data]." Tanpakushitsu Kakusan Koso 48(2): 167-72.
Brazma, A., K. Ikeo, et al. (2003). "[Standardization of microarray experiment data]." Tanpakushitsu Kakusan Koso 48(3): 280-5.
Burley, S. K. and J. B. Bonanno (2003). "Structural genomics." Methods Biochem Anal 44: 591-612.
Cheng, Q., S. Wang, et al. (2003). "New approaches for anti-infective drug discovery: antibiotics, vaccines and beyond." Curr Drug Targets Infect Disord 3(1): 66-75.
Infectious disease is the leading cause of death worldwide, and billions of dollars are invested every year in developing anti-infective drugs. In the meantime, resistant bacteria are on the steady rise and render many once effective drugs useless. The tremendous funding and the urgent need to treat the resistant bacterial infections lead to the rapid progress on development of new drugs and potential new drug targets. New discoveries are being made that increase our understanding of microbial pathogenesis. Technological advancement is also being made to accelerate the drug discovery process. This review will mainly focus on discussing novel strategies on the development of antibiotics and vaccines for treating bacterial infections. Details of how some of the emerging technologies such as genomics and bioinformatics are accelerating the drug discovery process will be highlighted. Newly emerging concepts in controlling bacterial infections such as the use of probiotics and enzybiotics will also be briefly described.
Chivian, D., T. Robertson, et al. (2003). "Ab initio methods." Methods Biochem Anal 44: 547-57.
Conway, T. and G. K. Schoolnik (2003). "Microarray expression profiling: capturing a genome-wide portrait of the transcriptome." Mol Microbiol 47(4): 879-89.
The bacterial transcriptome is a dynamic entity that reflects the organism's immediate, ongoing and genome-wide response to its environment. Microarray expression profiling provides a comprehensive portrait of the transcriptional world enabling us to view the organism as a 'system' that is more than the sum of its parts. The vigilance of microorganisms to environmental change, the alacrity of the transcriptional response, the short half-life of bacterial mRNA and the genome-scale nature of the investigation collectively explain the power of this method. These same features pose the most significant experimental design and execution issues which, unless surmounted, predictably generate a distorted image of the transcriptome. Conversely, the expression profile of a properly conceived and conducted microarray experiment can be used for hypothesis testing: disclosure of the metabolic and biosynthetic pathways that underlie adaptation of the organism to chang-ing conditions of growth; the identification of co-ordinately regulated genes; the regulatory circuits and signal transduction systems that mediate the adaptive response; and temporal features of developmental programmes. The study of bacterial pathogenesis by microarray expression profiling poses special challenges and opportunities. Although the technical hurdles are many, obtaining expression profiles of an organism growing in tissue will probably reveal strategies for growth and survival in the host's microenvironment. Identifying these colonization strategies and their cognate expression patterns involves a 'deconstruction' process that combines bioinformatics analysis and in vitro DNA array experimentation.
Counsell, D. (2003). "A review of bioinformatics education in the UK." Brief Bioinform 4(1): 7-21.
If the completion of the first draft of the human genome represents the coming of age of bioinformatics, then the emergence of bioinformatics as a university degree subject represents its establishment. In this paper bioinformatics as a subject for formal study is discussed, rather than as a subject for research, and a selection of the taught, mainly graduate, courses currently available in the UK are reviewed. Throughout, the author tries to draw parallels between the integration of bioinformatics into biomedical research and teaching today, and that of molecular biology, two decades ago. Others have made this analogy between these two relatively young disciplines. Although research sources are referenced, the author makes no pretence of objectivity. This article contains his opinions, and those of a number of current bioinformatics course organisers whose comments on the subject were solicited in advance specifically for this paper. The course organisers kindly advised how they planned their curricula, and described the special strengths of their programmes. Comments from present and former students of several bioinformatics degree programmes were also solicited. Except where individuals are directly quoted, any opinions expressed herein should be considered the author's. Compared with its sister piece [Marion Zatz, in previous issue of Briefings in Bioinformatics pp. 353], this paper is less about funding policy--which, in the UK, has lately (if belatedly) been more generous towards bioinformatics teaching--than it is about practice and content; the requirements of the bioinformatics research communities, the corresponding emphases of bioinformatics courses, and the general market for holders of bioinformatics degrees. Individual courses are cited throughout as examples, but the final section contains a full annotated listing with URL addresses. Based on the author's own experience of practising and teaching bioinformatics, he describes the skills he believes will be most useful to bioinformaticians in the near future and suggests ways to prepare students of bioinformatics for a fall in demand for those abilities.
Davidov, E., J. Holland, et al. (2003). "Advancing drug discovery through systems biology." Drug Discov Today 8(4): 175-83.
Pharmaceutical companies are facing an urgent need to both increase their lead compound and clinical candidate portfolios and satisfy market demands for continued innovation and revenue growth. Here, we outline an emerging approach that attempts to facilitate and alleviate many of the current drug discovery issues and problems. This is, in part, achieved through the systematic integration of technologies, which results in a superior output of data and information, thereby enhancing our understanding of biological function, chemico-biological interactions and, ultimately, drug discovery. Systems biology is one new discipline that is positioned to significantly impact this process.
Denslow, N., M. E. Michel, et al. (2003). "Application of proteomics technology to the field of neurotrauma." J Neurotrauma 20(5): 401-7.
Near-completion of the Human Genome Project has stimulated scientists to begin looking for the next step in unraveling normal and abnormal functions within biological systems. Consequently, there is new focus on the role of proteins in these processes. Proteomics is a burgeoning field that may provide a valuable approach to evaluate the post-traumatic central nervous system (CNS). Although we cannot provide a comprehensive assessment of all methods for protein analysis, this report summarizes some of the newer proteomic technologies that have propelled this field into the limelight and that are available to most researchers in neurotrauma. Three technical approaches (two-dimensional gel electrophoresis, direct analysis by mass spectrometry, including two-dimensional chromatography coupled to mass spectrometry and isotope coded affinity tags, and antibody technologies) are reviewed, and their advantages and disadvantages presented. A discussion of proteomic technology in the context of brain and spinal cord trauma follows, addressing current and future challenges. Proteomics will likely be very useful for developing diagnostic predictors after CNS injury and for mapping changes in proteins after injury in order to identify new therapeutic targets. Neurotrauma results in complex alterations to the biological systems within the nervous system, and these changes evolve over time. Exploration of the "new nervous system" that follows injury will require methods that can both fully assess and simplify this complexity.
Dreger, M. (2003). "Proteome analysis at the level of subcellular structures." Eur J Biochem 270(4): 589-99.
The targeting of proteins to particular subcellular sites is an important principle of the functional organization of cells at the molecular level. In turn, knowledge about the subcellular localization of a protein is a characteristic that may provide a hint as to the function of the protein. The combination of classic biochemical fractionation techniques for the enrichment of particular subcellular structures with the large-scale identification of proteins by mass spectrometry and bioinformatics provides a powerful strategy that interfaces cell biology and proteomics, and thus is termed 'subcellular proteomics'. In addition to its exceptional power for the identification of previously unknown gene products, the analysis of proteins at the subcellular level is the basis for monitoring important aspects of dynamic changes in the proteome such as protein transloction. This review summarizes data from recent subcellular proteomics studies with an emphasis on the type of data that can retrieved from such studies depending on the design of the analytical strategy.
Durand, D. (2003). "Vertebrate evolution: doubling and shuffling with a full deck." Trends Genet 19(1): 2-5.
The number and role of whole-genome duplications in vertebrate evolution has intrigued evolutionary biologists since Ohno first proposed genome duplication as the force driving the 'big leap' in vertebrate morphological innovation. Attempts to resolve these issues have been thwarted by small and noisy datasets, and by lack of computational accuracy and statistical rigor. Recently, Ken Wolfe and colleagues presented a genome-scale, statistically rigorous analysis of evidence based on the spatial organization of duplicated genes, as well as estimates of duplication times. Their results provide the strongest evidence to date of large-scale duplication throughout the vertebrate genome, consistent with at least one whole-genome duplication.
Eils, R. and C. Athale (2003). "Computational imaging in cell biology." J Cell Biol 161(3): 477-81.
Microscopy of cells has changed dramatically since its early days in the mid-seventeenth century. Image analysis has concurrently evolved from measurements of hand drawings and still photographs to computational methods that (semi-) automatically quantify objects, distances, concentrations, and velocities of cells and subcellular structures. Today's imaging technologies generate a wealth of data that requires visualization and multi-dimensional and quantitative image analysis as prerequisites to turning qualitative data into quantitative values. Such quantitative data provide the basis for mathematical modeling of protein kinetics and biochemical signaling networks that, in turn, open the way toward a quantitative view of cell biology. Here, we will review technologies for analyzing and reconstructing dynamic structures and processes in the living cell. We will present live-cell studies that would have been impossible without computational imaging. These applications illustrate the potential of computational imaging to enhance our knowledge of the dynamics of cellular structures and processes.
Elkin, P. L. (2003). "Primer on medical genomics part V: bioinformatics." Mayo Clin Proc 78(1): 57-64.
Bioinformatics is the discipline that develops and applies informatics to the field of molecular biology. Although a comprehensive review of the entire field of bioinformatics is beyond the scope of this article, I review the basic tenets of the field and provide a topical sampling of the popular technologies available to clinicians and researchers. These technologies include tools and methods for sequence analysis (nucleotide and protein sequences), rendering of secondary and tertiary structures for these molecules, and protein fold prediction that can lead to rational drug design. I then discuss signaling pathways, new standards for data representation of genes and proteins, and finally the promise of merging these molecular data with the clinical world (the new science of phenomics).
Fauman, E. B., A. L. Hopkins, et al. (2003). "Structural bioinformatics in drug discovery." Methods Biochem Anal 44: 477-97.
Fiehn, O. and W. Weckwerth (2003). "Deciphering metabolic networks." Eur J Biochem 270(4): 579-88.
All higher organisms divide major biochemical steps into different cellular compartments and often use tissue-specific division of metabolism for the same purpose. Such spatial resolution is accompanied with temporal changes of metabolite synthesis in response to environmental stimuli or developmental needs. Although analyses of primary and secondary gene products, i.e. transcripts, proteins, and metabolites, regularly do not cope with this spatial and temporal resolution, these gene products are often observed to be highly coregulated forming complex networks. Methods to study such networks are reviewed with respect to data acquisition, network statistics, and biochemical interpretation.
Fischer, W. B. (2003). "Computational bioanalysis of proteins." Anal Bioanal Chem 375(1): 23-5.
Frazer, K. A., L. Elnitski, et al. (2003). "Cross-species sequence comparisons: a review of methods and available resources." Genome Res 13(1): 1-12.
With the availability of whole-genome sequences for an increasing number of species, we are now faced with the challenge of decoding the information contained within these DNA sequences. Comparative analysis of DNA sequences from multiple species at varying evolutionary distances is a powerful approach for identifying coding and functional noncoding sequences, as well as sequences that are unique for a given organism. In this review, we outline the strategy for choosing DNA sequences from different species for comparative analyses and describe the methods used and the resources publicly available for these studies.
Fujio, S. and J. Azuma (2003). "[Current status of tailor-made medicine and the role of clinical pharmacology]." Nippon Yakurigaku Zasshi 121(3): 192-4.
Gadek, T. R. and J. B. Nicholas (2003). "Small molecule antagonists of proteins." Biochem Pharmacol 65(1): 1-8.
The identification of small molecule antagonists of protein function is at the core of the pharmaceutical industry. Successful approaches to this problem, including screening and rational design, have been developed over the years to identify antagonists of enzymes and cellular receptors. These methods have been extended to the search for inhibitors of protein-protein interactions. While the very possibility of designing a small molecule inhibitor for such interactions was once doubted, there are examples of such inhibitors that are currently marketed products and many more inhibitors in various stages of research and development. Here we review the progress in identifying and designing small molecule protein inhibitors, with particular attention to those that block protein-protein interactions. We also discuss the physical character of protein-protein interfaces, and the resulting implications for small molecule lead discovery and design.
Glazko, G. V., E. V. Koonin, et al. (2003). "A significant fraction of conserved noncoding DNA in human and mouse consists of predicted matrix attachment regions." Trends Genet 19(3): 119-24.
Noncoding DNA in the human-mouse orthologous intergenic regions contains "islands" of conserved sequences, the functions of which remain largely unknown. We hypothesized that some of these regions might be matrix-scaffold attachment regions, MARs (or S/MARs). MARs comprise one of the few classes of eukaryotic noncoding DNA with an experimentally characterized function, being involved in the attachment of chromatin to the nuclear matrix, chromatin remodeling and transcription regulation. To test our hypothesis, we analyzed the co-occurrence of predicted MARs with highly conserved noncoding DNA regions in human-mouse genomic alignments. We found that 11% of the conserved noncoding DNA consists of predicted MARs. Conversely, more than half of the predicted MARs co-occur with one or more independently identified conserved sequence blocks. An excess of conserved predicted MARs is seen in intergenic regions preceding 5' ends of genes, suggesting that these MARs are primarily involved in transcriptional control.
Godzik, A. (2003). "Fold recognition methods." Methods Biochem Anal 44: 525-46.
We are still missing a basic understanding of sequence/structure/function relationships in proteins. Analogy-based prediction algorithms remain the only reliable fold prediction tools. New methods, such as threading and hybrid threading/sequence fold recognition, can often recognize even the most distant homologues and, in some cases, even unrelated proteins with similar overall structures. This knowledge pushed the envelope of analogy-based function analysis to the point that the majority of newly sequenced genomes can be tentatively assigned to already characterized protein superfamilies. However, at this evolutionary distance, fold prediction is no longer equivalent to function prediction. Instead of having the same exact function, distantly related proteins might share some functional analogy that is not obvious to the casual observer. The main challenge facing the fold recognition field is to develop tools to follow the structure prediction with function prediction and analysis.
Heckel, D. G. (2003). "Genomics in pure and applied entomology." Annu Rev Entomol 48: 235-60.
Genomics is the study of the structure and function of the genome: the set of genetic information encoded in the DNA of the nucleus and organelles of an organism. It is a dynamic field that combines traditional paths of inquiry with new approaches that would have been impossible without recent technological developments. Much of the recent focus has been on obtaining the sequence of entire genomes, determining the order and organization of the genes, and developing libraries that provide immediate physical access to any desired DNA fragment. This has enabled functional studies on a genome-wide level, including analysis of the genetic basis of complex traits, quantification of global patterns of gene expression, and systematic gene disruption projects. The successful contribution of genomics to problems in applied entomology requires the cooperation of the private and public sectors to build upon the knowledge derived from the Drosophila genome and effectively develop models for other insect Orders.
Hood, L. and D. Galas (2003). "The digital code of DNA." Nature 421(6921): 444-8.
The discovery of the structure of DNA transformed biology profoundly, catalysing the sequencing of the human genome and engendering a new view of biology as an information science. Two features of DNA structure account for much of its remarkable impact on science: its digital nature and its complementarity, whereby one strand of the helix binds perfectly with its partner. DNA has two types of digital information--the genes that encode proteins, which are the molecular machines of life, and the gene regulatory networks that specify the behaviour of the genes.
Jackson, D. B., E. Minch, et al. (2003). "Bioinformatics." Exs(93): 31-69.
Jacoby, E., J. Davies, et al. (2003). "Design of small molecule libraries for NMR screening and other applications in drug discovery." Curr Top Med Chem 3(1): 11-23.
There are conceptual differences between high-throughput screening (HTS) and fragment-based screening by NMR. The number of compounds in libraries for NMR screening may be significantly smaller than those used for HTS. Because one relies on a small library its design is significantly important and is the object of this article. A short introduction on fragment-based NMR screening approaches will be provided. Although there are currently very few reports describing the design of libraries of small molecules for NMR screening, aspects of the question of how to compile diverse collections of small molecular fragments useful for drug design were previously addressed for the purposes of combinatorial library design and de novo drug design. As these disciplines are highly interrelated and are applied in an interconnected manner with NMR screening within the drug discovery process, a review of combinatorial library design and especially the building block or fragment selection strategies applied for combinatorial library design and de novo design is well suited to reveal fundamental strategies and potential techniques for the design of NMR screening libraries. This section will be rounded off by a report on hands-on-experience with the design of the Novartis second-site NMR screening library and practical considerations for the design of compound mixtures. Rather than providing an exact protocol general guidelines will be indicated.
Kanehisa, M. and P. Bork (2003). "Bioinformatics in the post-sequence era." Nat Genet 33 Suppl: 305-10.
In the past decade, bioinformatics has become an integral part of research and development in the biomedical sciences. Bioinformatics now has an essential role both in deciphering genomic, transcriptomic and proteomic data generated by high-throughput experimental technologies and in organizing information gathered from traditional biology. Sequence-based methods of analyzing individual genes or proteins have been elaborated and expanded, and methods have been developed for analyzing large numbers of genes or proteins simultaneously, such as in the identification of clusters of related genes and networks of interacting proteins. With the complete genome sequences for an increasing number of organisms at hand, bioinformatics is beginning to provide both conceptual bases and practical methods for detecting systemic functional behaviors of the cell and the organism.
Kellogg, G. E. and S. F. Semus (2003). "3D QSAR in modern drug design." Exs(93): 223-41.
Kort, E. J., B. Campbell, et al. (2003). "A human tissue and data resource: an overview of opportunities, challenges, and development of a provider/researcher partnership model." Comput Methods Programs Biomed 70(2): 137-50.
As we continue to strive to apply the findings of in vitro and animal studies to human disease and transition from genomics to proteomics, we will experience an ever-increasing need for human tissues. A web based system that provides access to tissues repositories and associated data will best facilitate the access to these vital resources and the application of research information to human disease treatment. There are organizational and design requirements that must be addressed in the implementation of the infrastructures that are needed to implement such a system, with special attention paid to the protection of patient anonymity. This report describes the implementation of a prototype human tissue network in the hope of encouraging implementation of similar systems among other consortia of providers and researchers.
Krieger, E., S. B. Nabuurs, et al. (2003). "Homology modeling." Methods Biochem Anal 44: 509-23.
Kriventseva, E. V., I. Koch, et al. (2003). "Increase of functional diversity by alternative splicing." Trends Genet 19(3): 124-8.
A large-scale analysis of protein isoforms arising from alternative splicing shows that alternative splicing tends to insert or delete complete protein domains more frequently than expected by chance, whereas disruption of domains and other structural modules is less frequent. If domain regions are disrupted, the functional effect, as predicted from 3D structure, is frequently equivalent to removal of the entire domain. Also, short alternative splicing events within domains, which might preserve folded structure, target functional residues more frequently than expected. Thus, it seems that positive selection has had a major role in the evolution of alternative splicing.
Krumrine, J., F. Raubacher, et al. (2003). "Principles and methods of docking and ligand design." Methods Biochem Anal 44: 443-76.
Lee, M. P. (2003). "Genome-wide analysis of epigenetics in cancer." Ann N Y Acad Sci 983: 101-9.
Human cancers are caused by multiple mechanisms. Research in the last 30 years has firmly established the roles of a group of genes including oncogenes, tumor suppressor genes, and DNA repair genes in human cancers. The activation and inactivation of these cancer genes can be caused by genetic mutations or epigenetic alterations. The epigenetic changes in cancers include methylation of CpG islands, loss of imprinting, and chromatin modification. The completion of the genome sequences of many organisms including the human has transformed the traditional approach to molecular biology research into an era of functional genome research. Traditional research usually involves the study of one or a few genes (proteins) in a particular biological process in normal physiology or disease. Functional genome research takes advantage of newly available genome sequences and high-throughput genome technologies to study genes and/or proteins to inform the perspective of entire biological processes. I will focus on recent progress in the identification of imprinted genes and methylation of CpG islands through genome-wide analysis.
Lio, P. (2003). "Statistical bioinformatic methods in microbial genome analysis." Bioessays 25(3): 266-73.
It is probable that, increasingly, genome investigations are going to be based on statistical formalization. This review summarizes the state of art and potentiality of using statistics in microbial genome analysis. First, I focus on recent advances in functional genomics, such as finding genes and operons, identifying gene conversion events, detecting DNA replication origins and analysing regulatory sites. Then I describe how to use phylogenetic methods in genome analysis and methods for genome-wide scanning for positively selected amino acids. I conclude with speculations on the future course of genome statistical modeling.
Lutke Holzik, M. F., R. H. Sijmons, et al. (2003). "Syndromic aspects of testicular carcinoma." Cancer 97(4): 984-92.
BACKGROUND: In patients with hereditary or constitutional chromosomal anomalies, testicular carcinoma can develop sporadically or on the basis of an underlying hereditary genetic defect. Greater knowledge of these genetic defects would provide more insight into the molecular pathways that lead to testicular carcinoma. To the authors' knowledge, little attention has been paid to date to the comorbid occurrence of testicular carcinoma in patients with hereditary disorders or constitutional chromosomal anomalies. METHODS: The authors performed a review of the literature. RESULTS: Twenty-five different hereditary disorders or constitutional chromosomal anomalies have been reported in patients who developed seminomatous or nonseminomatous testicular carcinoma. CONCLUSIONS: Although most of these malignancies were too rare to enable the detection of statistically significant correlations between the chromosomal/hereditary disorder and the testicular tumor, it was striking that many of the patients had also other urogenital abnormalities. Susceptibility to urogenital abnormalities seems to disrupt normal urogenital differentiation and suggests a correlation with testicular dysgenesis and, thus, also with testicular carcinoma. Other evidence of causal involvement has been found in the field of tumor cytogenetics. Some of the genes responsible for hereditary disorders have been mapped to regions that are of interest in the development of sporadic testicular carcinoma. Molecular studies on candidate genes will be required to provide definite answers. Completion of the human gene map and the availability of advanced gene arrays and bioinformatics are expected to greatly facilitate further exploration of the role of hereditary genetic defects in testicular carcinoma.
Machackova, E. (2003). "[Disease-causing mutations versus neutral polymorphism: use of bioinformatics and DNA diagnosis]." Cas Lek Cesk 142(3): 150-3.
Molecular genetic diagnostics is available for increasing number of genetically determined diseases. A wide spectrum of mutations can be detected by laboratory methods. A mutation can be defined as a change in a specific DNA sequence when compared with the reference sequence published in the gene database. However, in some cases it is difficult to distinguish if the detected sequence variant is a causal mutation or a neutral (polymorphic) variation without any effect on phenotype. The interpretation of rare sequence variants of unknown significance detected in disease-causing genes becomes an increasingly important problem. Further analysis on DNA and on protein levels with the use of bioinformatics are needed to reveal the effect of rare sequence variants. Inherited complex disorders, for example rare hereditary forms of cancer diseases, represent a challenge to molecular geneticists. The identification of exact causal mutation directly responsible for the development of the disease and for the assessment of disease risk resulting from this genetic variation has further implications. Predictive genetic diagnostics allows identify relatives at high risk of genetically determined disease and use of targeted preventive and therapeutic approaches. In severe cases it allows also prenatal or pre-implantation diagnostics.
Markley, J. L., E. L. Ulrich, et al. (2003). "Macromolecular structure determination by NMR spectroscopy." Methods Biochem Anal 44: 89-113.
Matter, H. (2003). "Computational approaches towards the quantification of molecular diversity and design of compound libraries." Exs(93): 125-56.
Murphy, S. K. and R. L. Jirtle (2003). "Imprinting evolution and the price of silence." Bioessays 25(6): 577-88.
In contrast to the biallelic expression of most genes, expression of genes subject to genomic imprinting is monoallelic and based on the sex of the transmitting parent. Possession of only a single active allele can lead to deleterious health consequences in humans. Aberrant expression of imprinted genes, through either genetic or epigenetic alterations, can result in developmental failures, neurodevelopmental and neurobehavioral disorders and cancer. The evolutionary emergence of imprinting occurred in a common ancestor to viviparous mammals after divergence from the egg-laying monotremes. Current evidence indicates that imprinting regulation in metatherian mammals differs from that in eutherian mammals. This suggests that imprinting mechanisms are evolving from those that were established 150 million years ago. Therefore, comparing genomic sequence of imprinted domains from marsupials and eutherians with those of orthologous regions in monotremes offers a potentially powerful bioinformatics approach for identifying novel imprinted genes and their regulatory elements. Such comparative studies will also further our understanding of the molecular evolution and phylogenetic distribution of imprinted genes.
Neidle, S., B. Schneider, et al. (2003). "Fundamentals of DNA and RNA structure." Methods Biochem Anal 44: 41-73.
Omata, M., M. Otsuka, et al. (2003). "[Study of digestive diseases in post-genome era]." Nippon Shokakibyo Gakkai Zasshi 100(2): 135-43.
Otsuka, M., Y. Hoshida, et al. (2003). "Liver chip and gene shaving." J Gastroenterol 38 Suppl 15: 89-92.
A comprehensive profile of genes expressed at the mRNA level in various human tissues is considered to be important for understanding the molecular mechanisms of the tissue-specific function and the pathogenesis of related diseases. Here, the gene expression profiling in three human digestive tissues, liver, stomach, and pancreas, was catalogued by generating a large number of expressed sequence tags, and clarified how quantitatively the gene expressions are different. After assembling the redundant clones among three tissues, the results showed that only 1.7% among the assembled genes was expressed commonly in the investigated tissues. These results suggest that the significant functional divergences in different tissues must be related to the divergence of the gene expression profiles. Recently, microarray technologies are widely used. Considering the results that different genes express in different tissues, however, it is important to spot the cDNAs derived from the same tissues or cells examined to acquire information efficiently. For the study of digestive diseases, we constructed an in-house microarray by using the cDNA sets derived from the digestive tissues (liver and gastric chip). In addition, because the amount of information acquired by the microarray analyses is huge, the power of bioinformatics for unifying the obtained data is indispensable. Some examples of the strategies for handling the microarray data obtained by our in-house microarrays are shown in this article.
Patterson, S. D. and R. H. Aebersold (2003). "Proteomics: the first decade and beyond." Nat Genet 33 Suppl: 311-23.
Proteomics is the systematic study of the many and diverse properties of proteins in a parallel manner with the aim of providing detailed descriptions of the structure, function and control of biological systems in health and disease. Advances in methods and technologies have catalyzed an expansion of the scope of biological studies from the reductionist biochemical analysis of single proteins to proteome-wide measurements. Proteomics and other complementary analysis methods are essential components of the emerging 'systems biology' approach that seeks to comprehensively describe biological systems through integration of diverse types of data and, in the future, to ultimately allow computational simulations of complex biological systems.
Pennacchio, L. A. and E. M. Rubin (2003). "Comparative genomic tools and databases: providing insights into the human genome." J Clin Invest 111(8): 1099-106.
Pires-daSilva, A. and R. J. Sommer (2003). "The evolution of signalling pathways in animal development." Nat Rev Genet 4(1): 39-49.
Despite the bewildering number of cell types and patterns found in the animal kingdom, only a few signalling pathways are required to generate them. Most cell-cell interactions during embryonic development involve the Hedgehog, Wnt, transforming growth factor-beta, receptor tyrosine kinase, Notch, JAK/STAT and nuclear hormone pathways. Looking at how these pathways evolved might provide insights into how a few signalling pathways can generate so much cellular and morphological diversity during the development of individual organisms and the evolution of animal body plans.
Plant, N. J. and G. G. Gibson (2003). "Evaluation of the toxicological relevance of CYP3A4 induction." Curr Opin Drug Discov Devel 6(1): 50-6.
CYP3A4 is the most abundant cytochrome P450 in human liver, comprising approximately 30% of the total liver P450 content. This enzyme has an important role in endogenous processes, most notably steroid catabolism, and also plays a fundamental role in the metabolism of more than half of the clinically used drugs currently prescribed. The majority of CYP3A substrates are also capable of upregulating CYP3A activity, mainly through transcriptional activation. The molecular mechanisms that underlie the transcriptional activation of CYP3A4 are complex, with many steroid hormone nuclear receptors, including GR, PXR, VDR and CAR, playing a role in these mechanisms. However, the net result of transcriptional activation is an increase in the metabolism of the inducing compounds and, therefore, increased clearance. An important side effect of this transcriptional activation is that co-administered chemicals metabolized by CYP3A may also have their pharmacokinetics altered. Such changes can result in reduced clinical efficacy of drugs, resulting in poor patient response, or the development of an adverse drug response. This review will examine examples of established interactions caused through transcriptional activation of CYP3A4, and speculate on whether such effects are clinically important and should be considered during the design of treatment regimes or, alternatively, are relatively minor and cause little physiological effects.
Puzyrev, V. P. (2003). "[Genetics of arterial hypertension (current research paradigms)]." Klin Med (Mosk) 81(1): 12-8.
Modern approaches to investigation of hypertension genetics are reviewed. These include genealogical, genetic-epidemiological, bioinformative methods, biological microchip technology. The results of genomic investigation of arterial hypertension are presented. Perspective lines in the research in the field of genetic cardiology are discussed.
Ressom, H., R. Reynolds, et al. (2003). "Increasing the efficiency of fuzzy logic-based gene expression data analysis." Physiol Genomics 13(2): 107-17.
DNA microarray technology can accommodate a multifaceted analysis of the expression of genes in an organism. The wealth of spatiotemporal data generated by this technology allows researchers to potentially reverse engineer a particular genetic network. "Fuzzy logic" has been proposed as a method to analyze the relationships between genes and help decipher a genetic network. This method can identify interacting genes that fit a known "fuzzy" model of gene interaction by testing all combinations of gene expression profiles. This paper introduces improvements made over previous fuzzy gene regulatory models in terms of computation time and robustness to noise. Improvement in computation time is achieved by using a cluster analysis as a preprocessing method to reduce the total number of gene combinations analyzed. This approach speeds up the algorithm by a factor of 50% with minimal effect on the results. The model's sensitivity to noise is reduced by implementing appropriate methods of "fuzzy rule aggregation" and "conjunction" that produce reliable results in the face of minor changes in model input.
Rost, B. (2003). "Prediction in 1D: secondary structure, membrane helices, and accessibility." Methods Biochem Anal 44: 559-87.
Salter, A. H. and K. C. Nilsson (2003). "Informatics and multivariate analysis of toxicogenomics data." Curr Opin Drug Discov Devel 6(1): 117-22.
The application of genomics methods to toxicology holds great promise. Toxicogenomics data mapping gene expression to predict toxicity and understand mechanisms are emerging, with data suggesting the possibility to classify, and eventually predict, toxic responses. The overall process of informatics analysis of microarray data is summarized. The relationship between the bioinformatics of gene expression and toxicogenomics is discussed, with reference to emerging themes that may be important as the field of toxicogenomics evolves. Emerging themes include the choice and validation of statistical methods, the use of gene annotation and the impact of genome sequence projects.
Scheeff, E. D. and J. L. Fink (2003). "Fundamentals of protein structure." Methods Biochem Anal 44: 15-39.
Schlecht, U. and M. Primig (2003). "Mining meiosis and gametogenesis with DNA microarrays." Reproduction 125(4): 447-56.
Gametogenesis is a key developmental process that involves complex transcriptional regulation of numerous genes including many that are conserved between unicellular eukaryotes and mammals. Recent expression-profiling experiments using microarrays have provided insight into the co-ordinated transcription of several hundred genes during mitotic growth and meiotic development in budding and fission yeast. Furthermore, microarray-based studies have identified numerous loci that are regulated during the cell cycle or expressed in a germ-cell specific manner in eukaryotic model systems like Caenorhabditis elegans, Mus musculus as well as Homo sapiens. The unprecedented amount of information produced by post-genome biology has spawned novel approaches to organizing biological knowledge using currently available information technology. This review outlines experiments that contribute to an emerging comprehensive picture of the molecular machinery governing sexual reproduction in eukaryotes.
Shih, J. Y., Y. C. Lee, et al. (2003). "Collapsin response mediator protein-1: a novel invasion-suppressor gene." Clin Exp Metastasis 20(1): 69-76.
Numerous genetic changes are associated with metastasis of cancer cells. Previously, we used microarray to identify that collapsin response mediator protein-1 (CRMP-1) was involved in cancer invasion and metastasis. We further characterized that CRMP-1 was a novel invasion-suppression gene. Members of the CRMP gene family are intracellular phosphoproteins involved in the mediation of semaphorin induced F-actin depolymerization and growth cone collapse. The precise mechanism by which CRMP-I inhibits invasion is not yet clear. However, CRMP-1 transfected cells had fewer filopodia and less Matrigel-invasion abilities. A low expression of CRMP-I mRNA in lung cancer tissue was significantly associated with advanced disease, lymph node metastasis, early post-operative relapse, and shorter survival. In this article, we reviewed the functions of CRMPs and semaphorins and analyzed the structure and motifs of CRMP-1 by bioinformatics. As such, we hoped to shed further light on the mechanism by which CRMP-1 suppresses the invasion of cancer cells.
Stanton, J. A., A. B. Macgregor, et al. (2003). "Gene expression in the mouse preimplantation embryo." Reproduction 125(4): 457-68.
Mouse preimplantation development represents a tightly controlled programme of gene expression and cell division, which starts with the fertilized egg and ends with implantation of the blastocyst approximately 4.5 days later. Spatial and temporal differences in gene expression underpin establishment of axes at the two-cell stage and development of the trophectoderm and inner cell mass after embryo compaction at the eight-cell stage. Approximately 15 700 mouse genes expressed during preimplantation development have been identified from cDNA sequences deposited in the UniGene database of the National Institutes of Health. This inventory of preimplantation genes is the starting point for identifying signalling modules that function in preimplantation development.
Stein, L. D. (2003). "Integrating biological databases." Nat Rev Genet 4(5): 337-45.
Recent years have seen an explosion in the amount of available biological data. More and more genomes are being sequenced and annotated, and protein and gene interaction data are accumulating. Biological databases have been invaluable for managing these data and for making them accessible. Depending on the data that they contain, the databases fulfil different functions. But, although they are architecturally similar, so far their integration has proved problematic.
Sumner, L. W., P. Mendes, et al. (2003). "Plant metabolomics: large-scale phytochemistry in the functional genomics era." Phytochemistry 62(6): 817-36.
Metabolomics or the large-scale phytochemical analysis of plants is reviewed in relation to functional genomics and systems biology. A historical account of the introduction and evolution of metabolite profiling into today's modern comprehensive metabolomics approach is provided. Many of the technologies used in metabolomics, including optical spectroscopy, nuclear magnetic resonance, and mass spectrometry are surveyed. The critical role of bioinformatics and various methods of data visualization are summarized and the future role of metabolomics in plant science assessed.
Takai, T. and T. Takagi (2003). "[Introduction to gene ontology]." Tanpakushitsu Kakusan Koso 48(1): 79-85.
Tan, P. T., A. M. Khan, et al. (2003). "Bioinformatics for venom and toxin sciences." Brief Bioinform 4(1): 53-62.
Venomous animals produce a myriad of important pharmacological components. The individual components, or venoms (toxins), are used in ion channel and receptor studies, drug discovery, and formulation of insecticides. The toxin data are scattered across public databases which provide sequence and structural descriptions, but very limited functional annotation. The exponential growth of newly identified toxin data has created a need for better data management. Venominformatics is a systematic bioinformatics approach in which classified, consolidated and cleaned venom data are stored into repositories and integrated with advanced bioinformatics tools for the analysis of structure and function of toxins. Venominformatics complements experimental studies and helps reduce the number of essential experiments.
Tate, J. (2003). "Molecular visualization." Methods Biochem Anal 44: 135-58.
Thanaraj, T. A. and S. Stamm (2003). "Prediction and statistical analysis of alternatively spliced exons." Prog Mol Subcell Biol 31: 1-31.
Valencia, A. and F. Pazos (2003). "Prediction of protein-protein interactions from evolutionary information." Methods Biochem Anal 44: 411-26.
van de Waterbeemd, H. (2003). "Physicochemical concepts in drug design." Exs(93): 243-57.
van Drie, J. H., D. C. Rohrer, et al. (2003). "Structure-based design of combinatorial libraries." Exs(93): 203-21.
Veselovsky, A. V. and A. S. Ivanov (2003). "Strategy of computer-aided drug design." Curr Drug Targets Infect Disord 3(1): 33-40.
Modern strategies of computer-aided drug design (CADD) are reviewed. The task of CADD in the pipeline of drug discovery is accelerating of finding the new lead compounds and their structure optimization for the following pharmacological tests. The main directions in CADD are based on the availability of the experimentally determined three-dimensional structure of the target macromolecule. If spatial structure is known the methods of structure-based drug design are used. In the opposite case the indirect methods of CADD based on the structures of known ligands (ligand-based drug design) are used. The interrelationship between the main directions of CADD is reviewed. The main CADD approaches of molecule de novo design and database mining are described. They include methods of molecular docking, de novo design, design of pharmacophore and quantity structure-activity relationship models. New ways and perspectives of CADD are discussed.
Vilar, J. M., C. C. Guet, et al. (2003). "Modeling network dynamics: the lac operon, a case study." J Cell Biol 161(3): 471-6.
We use the lac operon in Escherichia coli as a prototype system to illustrate the current state, applicability, and limitations of modeling the dynamics of cellular networks. We integrate three different levels of description (molecular, cellular, and that of cell population) into a single model, which seems to capture many experimental aspects of the system.
Volkmann, N. and D. Hanein (2003). "Electron microscopy." Methods Biochem Anal 44: 115-33.
Weiss, J. N., Z. Qu, et al. (2003). "Understanding biological complexity: lessons from the past." Faseb J 17(1): 1-6.
Advances in molecular biology now permit complex biological systems to be tracked at an exquisite level of detail. The information flow is so great, however, that using intuition alone to draw connections is unrealistic. Thus, the need to integrate mathematical biology with experimental biology is greater than ever. To achieve this integration, obstacles that have traditionally prevented effective communication between theoreticians and experimentalists must be overcome, so that experimentalists learn the language of mathematics and dynamical modeling and theorists learn the language of biology. Fifty years ago Alan Hodgkin and Andrew Huxley published their quantitative model of the nerve action potential; in the same year, Alan Turing published his work on pattern formation in activator-inhibitor systems. These classic studies illustrate two ends of the spectrum in mathematical biology: the detailed model approach and the minimal model approach. When combined, they are highly synergistic in analyzing the mechanisms underlying the behavior of complex biological systems. Their effective integration will be essential for unraveling the physical basis of the mysteries of life.
Wernisch, L. and S. J. Wodak (2003). "Identifying structural domains in proteins." Methods Biochem Anal 44: 365-85.
Wiley, H. S., S. Y. Shvartsman, et al. (2003). "Computational modeling of the EGF-receptor system: a paradigm for systems biology." Trends Cell Biol 13(1): 43-50.
Computational models have rarely been used as tools by biologists but, when models provide experimentally testable predictions, they can be extremely useful. The epidermal growth factor receptor (EGFR) is probably the best-understood receptor system, and computational models have played a significant part in its elucidation. For many years, models have been used to analyze EGFR dynamics and to interpret mutational studies, and are now being used to understand processes including signal transduction, autocrine loops and developmental patterning. The success of EGFR modeling can be a guide to combining models and experiments productively to understand complex biological processes as integrated systems.
Wilke, C. O. and C. Adami (2003). "Evolution of mutational robustness." Mutat Res 522(1-2): 3-11.
We review recent advances in the understanding of the mutation-selection balance of asexual replicators. For over 30 years, population geneticists thought that an expression derived by Kimura and Maruyama in 1966 fully solved this problem. However, Kimura and Maruyama's result is only correct in the absence of neutral mutations. The inclusion of neutral mutations leads to a wealth of interesting new effects, and, in particular, to a selective pressure to evolve robustness against mutations. We cover recent literature on the population dynamics of asexual replicators on networks of neutral genotypes, on the outcompetition of fast replicators by slower ones with better mutational support, and on the probability of fixation at high mutation rates. We discuss empirical evidence for the evolution of mutational robustness, and speculate on its relevance for higher organisms.
Wilson, D. S. and S. Nock (2003). "Recent developments in protein microarray technology." Angew Chem Int Ed Engl 42(5): 494-500.
The sequencing of the human genome and the advent of DNA chips and sophisticated bioinformatics platforms have enabled molecular biologists to take a more global view of biological systems and to analyze naturally occurring genetic variation. Microarrays of antibodies can measure the concentrations of many proteins quickly and simultaneously. Microarrays of genomically encoded proteins allow scientists to screen entire genomes for proteins that interact with particular factors, catalyze particular reactions, or act as substrates for protein-modifying enzymes or as targets of autoimmune responses. The new protein microarray platforms will prove invaluable to basic biological research, and will dramatically accelerate the pace of discovery of drug targets and diagnostic biomarkers.
Winslow, R. L. and M. S. Boguski (2003). "Genome informatics: current status and future prospects." Circ Res 92(9): 953-61.
This article reviews recent advances in genomics and informatics relevant to cardiovascular research. In particular, we review the status of (1) whole genome sequencing efforts in human, mouse, rat, zebrafish, and dog; (2) the development of data mining and analysis tools; (3) the launching of the National Heart, Lung, and Blood Institute Programs for Genomics Applications and Proteomics Initiative; (4) efforts to characterize the cardiac transcriptome and proteome; and (5) the current status of computational modeling of the cardiac myocyte. In each instance, we provide links to relevant sources of information on the World Wide Web and critical appraisals of the promises and the challenges of an expanding and diverse information landscape.
Wolfe, K. H. and W. H. Li (2003). "Molecular evolution meets the genomics revolution." Nat Genet 33 Suppl: 255-65.
Changes in technology in the past decade have had such an impact on the way that molecular evolution research is done that it is difficult now to imagine working in a world without genomics or the Internet. In 1992, GenBank was less than a hundredth of its current size and was updated every three months on a huge spool of tape. Homology searches took 30 minutes and rarely found a hit. Now it is difficult to find sequences with only a few homologs to use as examples for teaching bioinformatics. For molecular evolution researchers, the genomics revolution has showered us with raw data and the information revolution has given us the wherewithal to analyze it. In broad terms, the most significant outcome from these changes has been our newfound ability to examine the evolution of genomes as a whole, enabling us to infer genome-wide evolutionary patterns and to identify subsets of genes whose evolution has been in some way atypical.