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PubMed2001

Evolutionary dynamics of the human endogenous retrovirus family HERV-K inferred from full-length proviral genomes.

Several distinct families of endogenous retroviruses exist in the genomes of primates. Most of them are remnants of ancient germ-line infections. The human endogenous retrovirus family HERV-K represents the unique known case of endogenous retrovirus that amplified in the human genome after the divergence of human and chimpanzee lineages. There are two types of HERV-K proviral genomes differing by the presence or absence of 292 bp in the pol-env boundary. Human-specific insertions exist for both types. The analyses shown in the present work reveal that several lineages of type 1 and type 2 HERV-K proviruses remained transpositionally active after the human/chimpanzee split. The data also reflect the important role of mosaic evolution (either by recombination or gene conversion) during the evolutionary history of HERV-K.

Base Sequence↗

PubMed2003

Interdisciplinary sciences in the 21st century.

With the advance of genome projects the search for the order of cellular processes has become a realistic goal. Yet this order is hidden behind a screen of data, which obscures the actual connectivity of genes and proteins. In order to expose the true nature of these networks it becomes necessary to apply in silico analysis based on certain parallels between biological and complex technical systems. These efforts far exceed current notions of computational biology.

Computational Biology↗

PubMed2006

Computational prediction of cancer-gene function.

Most cancer genes remain functionally uncharacterized in the physiological context of disease development. High-throughput molecular profiling and interaction studies are increasingly being used to identify clusters of functionally linked gene products related to neoplastic cell processes. However, in vivo determination of cancer-gene function is laborious and inefficient, so accurately predicting cancer-gene function is a significant challenge for oncologists and computational biologists alike. How can modern computational and statistical methods be used to reliably deduce the function(s) of poorly characterized cancer genes from the newly available genomic and proteomic datasets? We explore plausible solutions to this important challenge.

Computational Biology↗

PubMed2004

The microRNA Registry.

The miRNA Registry provides a service for the assignment of miRNA gene names prior to publication. A comprehensive and searchable database of published miRNA sequences is accessible via a web interface (http://www.sanger.ac.uk/Software/Rfam/mirna/), and all sequence and annotation data are freely available for download. Release 2.0 of the database contains 506 miRNA entries from six organisms.

Animals↗

PubMed2001

Efficiency of database search for identification of mutated and modified proteins via mass spectrometry.

Although protein identification by matching tandem mass spectra (MS/MS) against protein databases is a widespread tool in mass spectrometry, the question about reliability of such searches remains open. Absence of rigorous significance scores in MS/MS database search makes it difficult to discard random database hits and may lead to erroneous protein identification, particularly in the case of mutated or post-translationally modified peptides. This problem is especially important for high-throughput MS/MS projects when the possibility of expert analysis is limited. Thus, algorithms that sort out reliable database hits from unreliable ones and identify mutated and modified peptides are sought. Most MS/MS database search algorithms rely on variations of the Shared Peaks Count approach that scores pairs of spectra by the peaks (masses) they have in common. Although this approach proved to be useful, it has a high error rate in identification of mutated and modified peptides. We describe new MS/MS database search tools, MS-CONVOLUTION and MS-ALIGNMENT, which implement the spectral convolution and spectral alignment approaches to peptide identification. We further analyze these approaches to identification of modified peptides and demonstrate their advantages over the Shared Peaks Count. We also use the spectral alignment approach as a filter in a new database search algorithm that reliably identifies peptides differing by up to two mutations/modifications from a peptide in a database.

Algorithms↗

PubMed1999

Biosequence exegesis.

Annotation of large-scale gene sequence data will benefit from comprehensive and consistent application of well-documented, standard analysis methods and from progressive and vigilant efforts to ensure quality and utility and to keep the annotation up to date. However, it is imperative to learn how to apply information derived from functional genomics and proteomics technologies to conceptualize and explain the behaviors of biological systems. Quantitative and dynamical models of systems behaviors will supersede the limited and static forms of single-gene annotation that are now the norm. Molecular biological epistemology will increasingly encompass both teleological and causal explanations.

Animals↗

PubMed2004

Network analysis of metabolic enzyme evolution in Escherichia coli.

BACKGROUND: The two most common models for the evolution of metabolism are the patchwork evolution model, where enzymes are thought to diverge from broad to narrow substrate specificity, and the retrograde evolution model, according to which enzymes evolve in response to substrate depletion. Analysis of the distribution of homologous enzyme pairs in the metabolic network can shed light on the respective importance of the two models. We here investigate the evolution of the metabolism in E. coli viewed as a single network using EcoCyc. RESULTS: Sequence comparison between all enzyme pairs was performed and the minimal path length (MPL) between all enzyme pairs was determined. We find a strong over-representation of homologous enzymes at MPL 1. We show that the functionally similar and functionally undetermined enzyme pairs are responsible for most of the over-representation of homologous enzyme pairs at MPL 1. CONCLUSIONS: The retrograde evolution model predicts that homologous enzymes pairs are at short metabolic distances from each other. In general agreement with previous studies we find that homologous enzymes occur close to each other in the network more often than expected by chance, which lends some support to the retrograde evolution model. However, we show that the homologous enzyme pairs which may have evolved through retrograde evolution, namely the pairs that are functionally dissimilar, show a weaker over-representation at MPL 1 than the functionally similar enzyme pairs. Our study indicates that, while the retrograde evolution model may have played a small part, the patchwork evolution model is the predominant process of metabolic enzyme evolution.

Algorithms↗

PubMed2006

Using information from public Arabidopsis databases to aid research.

The volume of Arabidopsis information has increased enormously in recent years as a result of the sequencing of the genome and other large-scale genomic projects. Much of the data are stored in public databases, where data are organized, analyzed, and made freely accessible to the research community. These databases are resources that researchers can utilize for making predictions and developing testable hypotheses. The methods in this chapter describe ways to access and utilize Arabidopsis data and genomic resources found in databases.

Access to Information↗

PubMed2000

NCBI genetic resources supporting immunogenetic research.

The NCBI creates and maintains a set of integrated bibliographic, sequence, map, structure and other database resources to promote the efficient retrieval of information and the discovery of novel relationships. The connections made between elements of these resources permit researchers to start a search from a wide spectrum of entry points. These multiple dimensions of data can be roughly categorized by primary content as text or bibliographic (PubMed, PubMedCentral, OMIM, LocusLink), sequence (GenBank, Reference Sequence Project (RefSeq), dbSNP, MMDB), protein structure (MMDB) or map position (MapView). They can also becategorized by level of expert curation, which may range from validation of submissions from external groups (GenBank, PubMed, PubMedCentral,), to automatic computation (HomoloGene, UniGene), and to highly reviewed and corrected (LocusLink, MMDB, OMIM, RefSeq). Searches can be made by words (in an article title, key words, sequence annotation, database value, author) by sequence (BLAST or e-PCR against multiple sequence databases), or by map coordinates. By computing or curating bi-directional links between related objects, NCBI can represent content on the genetics, molecular biology, and clinical considerations of interest to immunogeneticists. There is also an emerging resource developed by the NCBI in collaboration with the IHWG devoted to the presentation of MHC data (dbMHC). How dbMHC will augment existing resources at the NCBI is described.

Computational Biology↗

PubMed2005

New friendly tools for users of ESTHER, the database of the alpha/beta-hydrolase fold superfamily of proteins.

The structural alpha/beta-hydrolase fold is characterized by a beta-sheet core of five to eight strands connected by alpha-helices to form a alpha/beta/alpha sandwich. The superfamily members, exemplified by the cholinesterases, diverged from a common ancestor into a number of hydrolytic enzymes displaying a wide range of substrate specificities, along with proteins with no recognized hydrolytic activity. In the enzymes, the catalytic triad residues are presented on loops of which one, the nucleophile elbow, is the most conserved feature of the fold. Of the other proteins, which all lack from one to all of the catalytic residues, some may simply be 'inactive' enzymes while others have been shown to be involved in heterologous surface recognition functions. The ESTHER (for esterases, alpha/beta-hydrolase enzymes and relatives) database (http://bioweb.ensam.inra.fr.esther) gathers and annotates all the published pieces of information (gene and protein sequences; biochemical, pharmacological, and structural data) related to the superfamily, and connects them together to provide the bases for studying structure-function relationships within the superfamily. The most recent developments of the database are presented.

Cholinesterases↗

PubMed2002

To 5D and beyond: quantitative fluorescence microscopy in the postgenomic era.

Digital fluorescence microscopy is now a standard technology for assaying molecular localisation in cells and tissues. The choice of laser scanning (LSM) and wide-field microscopes (WFM) largely depends on the type of sample, with LSMs performing best on thick samples and WFMs performing best on thin ones. These systems are increasingly used to collect large multidimensional datasets. We propose a unified image structure that considers space, time, and fluorescence wavelength as integral parts of the image. Moreover, the application of fluorescence imaging to large-scale screening means that large datasets are now routinely acquired. We propose that analysis of these data requires querying tools based on relational databases and describe one such system.

Animals↗

PubMed2000

Exploring protein domain structure.

The protein databank contains coordinates of over 10,000 protein structures, which constitute more than 25,000 structural domains in total. The investigation of protein structural, functional and evolutionary relationships is fundamental to many important fields in bioinformatics research, and will be crucial in determining the function of the human and other genomes. This review describes the SCOP and CATH databases of protein structure classification, which define, classify and annotate each domain in the protein databank. The hierarchical structure, use and annotation of the databases are explained. Other tools for exploring protein structure relationships are also described.

Computational Biology↗

PubMed2000

A simple probabilistic scoring method for protein domain identification.

SUMMARY: A simple heuristic scoring method is described for assigning sequences to known domain types based on BLAST search outputs. The scoring is based on the score distribution of the known domain groups determined from a database versus database comparison and is directly applicable to BLAST output processing.

Computational Biology↗

PubMed2001

Database-driven multi locus sequence typing (MLST) of bacterial pathogens.

MOTIVATION: Multi Locus Sequence Typing (MLST) is a newly developed typing method for bacteria based on the sequence determination of internal fragments of seven house-keeping genes. It has proved useful in characterizing and monitoring disease-causing and antibiotic resistant lineages of bacteria. The strength of this approach is that unlike data obtained using most other typing methods, sequence data are unambiguous, can be held on a central database and be queried through a web server. RESULTS: A database-driven software system (mlstdb) has been developed, which is used by public health laboratories and researchers globally to query their nucleotide sequence data against centrally held databases over the internet. The mlstdb system consists of a set of perl scripts for defining the database tables and generating the database management interface and dynamic web pages for querying the databases. AVAILABILITY: http://www.mlst.net.

Bacteria↗

PubMed2003

Predicting the topology of transmembrane helical proteins using mean burial propensity and a hidden-Markov-model-based method.

Helices in membrane spanning regions are more tightly packed than the helices in soluble proteins. Thus, we introduce a method that uses a simple scale of burial propensity and a new algorithm to predict transmembrane helical (TMH) segments and a positive-inside rule to predict amino-terminal orientation. The method (the topology predictor of transmembrane helical proteins using mean burial propensity [THUMBUP]) correctly predicted the topology of 55 of 73 proteins (or 75%) with known three-dimensional structures (the 3D helix database). This level of accuracy can be reached by MEMSAT 1.8 (a 200-parameter model-recognition method) and a new HMM-based method (a 111-parameter hidden Markov model, UMDHMM(TMHP)) if they were retrained with the 73-protein database. Thus, a method based on a physiochemical property can provide topology prediction as accurate as those methods based on more complicated statistical models and learning algorithms for the proteins with accurately known structures. Commonly used HMM-based methods and MEMSAT 1.8 were trained with a combination of the partial 3D helix database and a 1D helix database of TMH proteins in which topology information were obtained by gene fusion and other experimental techniques. These methods provide a significantly poorer prediction for the topology of TMH proteins in the 3D helix database. This suggests that the 1D helix database, because of its inaccuracy, should be avoided as either a training or testing database. A Web server of THUMBUP and UMDHMM(TMHP) is established for academic users at http://www.smbs.buffalo.edu/phys_bio/service.htm. The 3D helix database is also available from the same Web site.

Algorithms↗

PubMed2006

Developmental mouse brain gene expression maps.

Brain gene expression databases are providing an increasing amount of information to the neuroscience community. Most databases are focused on the adult mouse rather than embryonic development. Here we survey the major mouse gene expression databases for the developing brain. The high throughput in situ hybridization approach generates large volumes of gene expression data that can be compiled and examined in a relatively short period of time. It is of increasing importance to compare gene expression patterns of neurodevelopment in the brain in relation to the adult. Often clues to adult gene expression and gene function can be determined by examining embryonic development. It is our hope that once all genes are mapped in the brain from the embryo to the adult, studies can be conducting based on information derived from such databases in conjunction with other bioinformatics sources.

Animals↗

PubMed2006

Analysis of the genome-wide variations among multiple strains of the plant pathogenic bacterium Xylella fastidiosa.

BACKGROUND: The Gram-negative, xylem-limited phytopathogenic bacterium Xylella fastidiosa is responsible for causing economically important diseases in grapevine, citrus and many other plant species. Despite its economic impact, relatively little is known about the genomic variations among strains isolated from different hosts and their influence on the population genetics of this pathogen. With the availability of genome sequence information for four strains, it is now possible to perform genome-wide analyses to identify and categorize such DNA variations and to understand their influence on strain functional divergence. RESULTS: There are 1,579 genes and 194 non-coding homologous sequences present in the genomes of all four strains, representing a 76. 2% conservation of the sequenced genome. About 60% of the X. fastidiosa unique sequences exist as tandem gene clusters of 6 or more genes. Multiple alignments identified 12,754 SNPs and 14,449 INDELs in the 1528 common genes and 20,779 SNPs and 10,075 INDELs in the 194 non-coding sequences. The average SNP frequency was 1.08 x 10(-2) per base pair of DNA and the average INDEL frequency was 2.06 x 10(-2) per base pair of DNA. On an average, 60.33% of the SNPs were synonymous type while 39.67% were non-synonymous type. The mutation frequency, primarily in the form of external INDELs was the main type of sequence variation. The relative similarity between the strains was discussed according to the INDEL and SNP differences. The number of genes unique to each strain were 60 (9a5c), 54 (Dixon), 83 (Ann1) and 9 (Temecula-1). A sub-set of the strain specific genes showed significant differences in terms of their codon usage and GC composition from the native genes suggesting their xenologous origin. Tandem repeat analysis of the genomic sequences of the four strains identified associations of repeat sequences with hypothetical and phage related functions. CONCLUSION: INDELs and strain specific genes have been identified as the main source of variations among strains, with individual strains showing different rates of genome evolution. Based on these genome comparisons, it appears that the Pierce's disease strain Temecula-1 genome represents the ancestral genome of the X. fastidiosa. Results of this analysis are publicly available in the form of a web database.

Analysis of Variance↗

PubMed1999

INTERACT: an object oriented protein-protein interaction database.

MOTIVATION: Protein-protein interactions provide vital information concerning the function of proteins, complexes and networks. Currently there is no widely accepted repository of this interaction information. Our aim is to provide a single database with the necessary architecture to fully store, query and analyse interaction data. RESULTS: An object oriented database has been created which provides scientists with a resource for examining existing protein-protein interactions and inferring possible interactions from the data stored. It also provides a basis for examining networks of interacting proteins, via analysis of the data stored. The database contains over a thousand interactions. CONTACT: k.eilbeck@stud.man.ac.uk

Computational Biology↗