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PubMed2005

BioContrasts: extracting and exploiting protein-protein contrastive relations from biomedical literature.

MOTIVATION: Contrasts are useful conceptual vehicles for learning processes and exploratory research of the unknown. For example, contrastive information between proteins can reveal what similarities, divergences and relations there are of the two proteins, leading to invaluable insights for better understanding about the proteins. Such contrastive information are found to be reported in the biomedical literature. However, there have been no reported attempts in current biomedical text mining work that systematically extract and present such useful contrastive information from the literature for exploitation. RESULTS: Our BioContrasts system extracts protein-protein contrastive information from MEDLINE abstracts and presents the information to biologists in a web-application for exploitation. Contrastive information are identified in the text abstracts with contrastive negation patterns such as 'A but not B'. A total of 799 169 pairs of contrastive expressions were successfully extracted from 2.5 million MEDLINE abstracts. Using grounding of contrastive protein names to Swiss-Prot entries, we were able to produce 41 471 pieces of contrasts between Swiss-Prot protein entries. These contrastive pieces of information are then presented via a user-friendly interactive web portal that can be exploited for applications such as the refinement of biological pathways. AVAILABILITY: BioContrasts can be accessed at http://biocontrasts.i2r.a-star.edu.sg. It is also mirrored at http://biocontrasts.biopathway.org. SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.

Artificial Intelligence↗
PubMed2006

CFinder: locating cliques and overlapping modules in biological networks.

UNLABELLED: Most cellular tasks are performed not by individual proteins, but by groups of functionally associated proteins, often referred to as modules. In a protein association network modules appear as groups of densely interconnected nodes, also called communities or clusters. These modules often overlap with each other and form a network of their own, in which nodes (links) represent the modules (overlaps). We introduce CFinder, a fast program locating and visualizing overlapping, densely interconnected groups of nodes in undirected graphs, and allowing the user to easily navigate between the original graph and the web of these groups. We show that in gene (protein) association networks CFinder can be used to predict the function(s) of a single protein and to discover novel modules. CFinder is also very efficient for locating the cliques of large sparse graphs. AVAILABILITY: CFinder (for Windows, Linux and Macintosh) and its manual can be downloaded from http://angel.elte.hu/clustering. SUPPLEMENTARY INFORMATION: Supplementary data are available on Bioinformatics online.

Biology↗
PubMed2006

TFAM detects co-evolution of tRNA identity rules with lateral transfer of histidyl-tRNA synthetase.

We present TFAM, an automated, statistical method to classify the identity of tRNAs. TFAM, currently optimized for bacteria, classifies initiator tRNAs and predicts the charging identity of both typical and atypical tRNAs such as suppressors with high confidence. We show statistical evidence for extensive variation in tRNA identity determinants among bacterial genomes due to variation in overall tDNA base content. With TFAM we have detected the first case of eukaryotic-like tRNA identity rules in bacteria. An alpha-proteobacterial clade encompassing Rhizobiales, Caulobacter crescentus and Silicibacter pomeroyi, unlike a sister clade containing the Rickettsiales, Zymomonas mobilis and Gluconobacter oxydans, uses the eukaryotic identity element A73 instead of the highly conserved prokaryotic element C73. We confirm divergence of bacterial histidylation rules by demonstrating perfect covariation of alpha-proteobacterial tRNA(His) acceptor stems and residues in the motif IIb tRNA-binding pocket of their histidyl-tRNA synthetases (HisRS). Phylogenomic analysis supports lateral transfer of a eukaryotic-like HisRS into the alpha-proteobacteria followed by in situ adaptation of the bacterial tDNA(His) and identity rule divergence. Our results demonstrate that TFAM is an effective tool for the bioinformatics, comparative genomics and evolutionary study of tRNA identity.

Alphaproteobacteria↗
PubMed2006

HotSwap for bioinformatics: a STRAP tutorial.

BACKGROUND: Bioinformatics applications are now routinely used to analyze large amounts of data. Application development often requires many cycles of optimization, compiling, and testing. Repeatedly loading large datasets can significantly slow down the development process. We have incorporated HotSwap functionality into the protein workbench STRAP, allowing developers to create plugins using the Java HotSwap technique. RESULTS: Users can load multiple protein sequences or structures into the main STRAP user interface, and simultaneously develop plugins using an editor of their choice such as Emacs. Saving changes to the Java file causes STRAP to recompile the plugin and automatically update its user interface without requiring recompilation of STRAP or reloading of protein data. This article presents a tutorial on how to develop HotSwap plugins. STRAP is available at http://strapjava.de and http://www.charite.de/bioinf/strap. CONCLUSION: HotSwap is a useful and time-saving technique for bioinformatics developers. HotSwap can be used to efficiently develop bioinformatics applications that require loading large amounts of data into memory.

Algorithms↗
PubMed2006

Mycobacterium tuberculosis complex genetic diversity: mining the fourth international spoligotyping database (SpolDB4) for classification, population genetics and epidemiology.

BACKGROUND: The Direct Repeat locus of the Mycobacterium tuberculosis complex (MTC) is a member of the CRISPR (Clustered regularly interspaced short palindromic repeats) sequences family. Spoligotyping is the widely used PCR-based reverse-hybridization blotting technique that assays the genetic diversity of this locus and is useful both for clinical laboratory, molecular epidemiology, evolutionary and population genetics. It is easy, robust, cheap, and produces highly diverse portable numerical results, as the result of the combination of (1) Unique Events Polymorphism (UEP) (2) Insertion-Sequence-mediated genetic recombination. Genetic convergence, although rare, was also previously demonstrated. Three previous international spoligotype databases had partly revealed the global and local geographical structures of MTC bacilli populations, however, there was a need for the release of a new, more representative and extended, international spoligotyping database. RESULTS: The fourth international spoligotyping database, SpolDB4, describes 1939 shared-types (STs) representative of a total of 39,295 strains from 122 countries, which are tentatively classified into 62 clades/lineages using a mixed expert-based and bioinformatical approach. The SpolDB4 update adds 26 new potentially phylogeographically-specific MTC genotype families. It provides a clearer picture of the current MTC genomes diversity as well as on the relationships between the genetic attributes investigated (spoligotypes) and the infra-species classification and evolutionary history of the species. Indeed, an independent Naïve-Bayes mixture-model analysis has validated main of the previous supervised SpolDB3 classification results, confirming the usefulness of both supervised and unsupervised models as an approach to understand MTC population structure. Updated results on the epidemiological status of spoligotypes, as well as genetic prevalence maps on six main lineages are also shown. Our results suggests the existence of fine geographical genetic clines within MTC populations, that could mirror the passed and present Homo sapiens sapiens demographical and mycobacterial co-evolutionary history whose structure could be further reconstructed and modelled, thereby providing a large-scale conceptual framework of the global TB Epidemiologic Network. CONCLUSION: Our results broaden the knowledge of the global phylogeography of the MTC complex. SpolDB4 should be a very useful tool to better define the identity of a given MTC clinical isolate, and to better analyze the links between its current spreading and previous evolutionary history. The building and mining of extended MTC polymorphic genetic databases is in progress.

Computational Biology↗
PubMed2026

Identifying JAK2 and ANXA5 as Key Genes Linking Obstructive Sleep Apnea and Oxidative Stress via Machine Learning and Multilayer Transcriptomic Integration With Functional Validation.

Obstructive sleep apnea (OSA) is a common and severe sleep disorder closely associated with oxidative stress (OS). This study aims to identify and validate potential OS-related genes associated with OSA through bioinformatics methods. We successfully identified OS-related differentially expressed genes (OS-DEGs) by combining the limma test, weighted correlation network analysis (WGCNA), and OS-related genes from the GeneCards database. Key genes and potential biological roles were further identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), enrichment analysis, protein-protein interaction (PPI) network analysis, Lasso regression analysis, random forest algorithm, and support vector machine recursive feature elimination (SVM-RFE) method. Evaluate and validate the accuracy of key genes through receiver operating characteristic (ROC) curve analysis. The human single-cell RNA sequencing (scRNA-seq) dataset is used for cell classification annotation, analysis of key gene single-cell expression profiles, and virtual gene knockout experiments based on the scTenifoldKnk algorithm. Integrating scRNA-seq sequencing, pseudotime trajectory inference, cell-cell communication analysis, and bulk immune infiltration deconvolution reveals monocyte subtype remodeling in OSA. Finally, the expression levels of key genes in clinical samples were validated using real-time quantitative PCR (RT-qPCR) and Western blotting. A total of 57 common DEGs, indicating significant enrichment in OS, inflammation, and tumor pathways, particularly prominent in the immunometabolism pathway. By integrating DEGs, WGCNA, PPI results, and machine learning methods, key genes Janus kinase 2 (JAK2) and ANXA5 were screened out. JAK2 was significantly upregulated under disease conditions, while ANXA5 was significantly downregulated. ROC curve exhibited high accuracy (area under the curve [AUC] > 0.85). Human scRNA-seq analysis revealed that key genes were predominantly highly expressed in monocytes. Virtual knockout experiments demonstrated that these key genes play a crucial role in regulating immune responses and inflammatory reactions. PPI networks and enrichment analysis verified that downstream genes S100P, ALOX5AP, PROK2, and PADI4 may collaboratively participate in immune response and inflammation regulation. Finally, clinical sample experiment further validated the results of bioinformatics analysis. This study provides new research insights for the diagnosis, mechanism research, and treatment development of OSA in the future by integrating multilayer transcriptomic and machine learning techniques.

Humans↗
PubMed1998

Bioinformatics: searching the Net.

During the past 30 years, there has been an explosion in the volume of published medical information. As this volume has increased, so has the need for efficient methods for searching the data. MEDLINE, the primary medical database, is currently limited to abstracts of the medical literature. MEDLINE searches use AND/OR/NOT logical searching for keywords that have been assigned to each article and for textwords included in article abstracts. Recently, the complete text of some scientific journals, including figures and tables, has become accessible electronically. Keyword and textword searches can provide an overwhelming number of results. Search engines that use phrase searching, or searches that limit the number of words between two finds, improve the precision of search engines. The development of the Internet as a vehicle for worldwide communication, and the emergence of the World Wide Web (WWW) as a common vehicle for communication have made instantaneous access to much of the entire body of medical information an exciting possibility. There is more than one way to search the WWW for information. At the present time, two broad strategies have emerged for cataloging the WWW: directories and search engines. These allow more efficient searching of the WWW. Directories catalog WWW information by creating categories and subcategories of information and then publishing pointers to information within the category listings. Directories are analogous to yellow pages of the phone book. Search engines make no attempt to categorize information. They automatically scour the WWW looking for words and then automatically create an index of those words. When a specific search engine is used, its index is searched for a particular word. Usually, search engines are nonspecific and produce voluminous results. Use of AND/OR/NOT and "near" and "adjacent" search refinements greatly improve the results of a search. Search engines that limit their scope to specific sites, and metasearch sites that use multiple search engines optimized for specific types of searches have recently emerged. The distinctions between search engines and directory searches have blurred. Eventually, conceptual searching in which the computer searches for related ideas, without having to be given all the related keywords, may become a reality. This will free the user from having to learn specific rules about searching, allowing energies to be focused on results of the search, not the search itself.

Computational Biology↗
PubMed2004

GMD@CSB.DB: the Golm Metabolome Database.

UNLABELLED: Metabolomics, in particular gas chromatography-mass spectrometry (GC-MS) based metabolite profiling of biological extracts, is rapidly becoming one of the cornerstones of functional genomics and systems biology. Metabolite profiling has profound applications in discovering the mode of action of drugs or herbicides, and in unravelling the effect of altered gene expression on metabolism and organism performance in biotechnological applications. As such the technology needs to be available to many laboratories. For this, an open exchange of information is required, like that already achieved for transcript and protein data. One of the key-steps in metabolite profiling is the unambiguous identification of metabolites in highly complex metabolite preparations from biological samples. Collections of mass spectra, which comprise frequently observed metabolites of either known or unknown exact chemical structure, represent the most effective means to pool the identification efforts currently performed in many laboratories around the world. Here we present GMD, The Golm Metabolome Database, an open access metabolome database, which should enable these processes. GMD provides public access to custom mass spectral libraries, metabolite profiling experiments as well as additional information and tools, e.g. with regard to methods, spectral information or compounds. The main goal will be the representation of an exchange platform for experimental research activities and bioinformatics to develop and improve metabolomics by multidisciplinary cooperation. AVAILABILITY: http://csbdb.mpimp-golm.mpg.de/gmd.html CONTACT: Steinhauser@mpimp-golm.mpg.de SUPPLEMENTARY INFORMATION: http://csbdb.mpimp-golm.mpg.de/

Database Management Systems↗
PubMed2006

TransportDB: a comprehensive database resource for cytoplasmic membrane transport systems and outer membrane channels.

TransportDB (http://www.membranetransport.org/) is a comprehensive database resource of information on cytoplasmic membrane transporters and outer membrane channels in organisms whose complete genome sequences are available. The complete set of membrane transport systems and outer membrane channels of each organism are annotated based on a series of experimental and bioinformatic evidence and classified into different types and families according to their mode of transport, bioenergetics, molecular phylogeny and substrate specificities. User-friendly web interfaces are designed for easy access, query and download of the data. Features of the TransportDB website include text-based and BLAST search tools against known transporter and outer membrane channel proteins; comparison of transporter and outer membrane channel contents from different organisms; known 3D structures of transporters, and phylogenetic trees of transporter families. On individual protein pages, users can find detailed functional annotation, supporting bioinformatic evidence, protein/DNA sequences, publications and cross-referenced external online resource links. TransportDB has now been in existence for over 10 years and continues to be regularly updated with new evidence and data from newly sequenced genomes, as well as having new features added periodically.

Bacterial Outer Membrane Proteins↗
PubMed2003

Bioinformatic and molecular analysis of hydroxymethylbutenyl diphosphate synthase (GCPE) gene expression during carotenoid accumulation in ripening tomato fruit.

Carotenoids are plastidic isoprenoid pigments of great biological and biotechnological interest. The precursors for carotenoid production are synthesized through the recently elucidated methylerythritol phosphate (MEP) pathway. Here we have identified a tomato ( Lycopersicon esculentum Mill.) cDNA sequence encoding a full-length protein with homology to the MEP pathway enzyme hydroxymethylbutenyl 4-diphosphate synthase (HDS, also called GCPE). Comparison with other plant and bacterial HDS sequences showed that the plant enzymes contain a plastid-targeting N-terminal sequence and two highly conserved plant-specific domains in the mature protein with no homology to any other sequence in the databases. The ubiquitous distribution of HDS-encoding expressed sequence tags (ESTs) in the tomato collections suggests that the corresponding gene is likely expressed throughout the plant. The role of HDS in controlling the supply of precursors for carotenoid biosynthesis was estimated from the bioinformatic and molecular analysis of transcript abundance in different stages of fruit development. No significant changes in HDS gene expression were deduced from the statistical analysis of EST distribution during fruit ripening, when an active MEP pathway is required to support a massive accumulation of carotenoids. RNA blot experiments confirmed that similar transcript levels were present in both the wild-type and carotenoid-depleted yellow ripe ( r) mutant fruit independent of the stage of development and the carotenoid composition of the fruit. Together, our results are consistent with a non-limiting role for HDS in carotenoid biosynthesis during tomato fruit ripening.

Amino Acid Sequence↗
PubMed1996

Gene expression in normal and disease states--identification of therapeutic targets.

Analysis of gene-expression patterns derived from large expressed sequence tag (EST) databases has become a valuable tool in the discovery of therapeutic targets and diagnostic markers. Sequence data derived from a wide variety of cDNA libraries offer a wealth of information for identifying genes for pharmaceutical product development. Collecting, storing, organizing, analyzing and presenting cDNA expression data requires advanced bioinformatics methods and high-performance computational equipment. Comparison of expression patterns from normal and disease tissues enables inferences about gene function to be made, and medically relevant genes as candidates for therapeutics research and development programs to be identified.

Biotechnology↗
PubMed2006

Identification and genetic mapping of highly polymorphic microsatellite loci from an EST database of the septoria tritici blotch pathogen Mycosphaerella graminicola.

A database of 30,137 EST sequences from Mycosphaerella graminicola, the septoria tritici blotch fungus of wheat, was scanned with a custom software pipeline for di- and trinucleotide units repeated tandemly six or more times. The bioinformatics analysis identified 109 putative SSR loci, and for 99 of them, flanking primers were developed successfully and tested for amplification and polymorphism by PCR on five field isolates of diverse origin, including the parents of the standard M. graminicola mapping population. Seventy-seven of the 99 primer pairs generated an easily scored banding pattern and 51 were polymorphic, with up to four alleles per locus, among the isolates tested. Among these 51 loci, 23 were polymorphic between the parents of the mapping population. Twenty-one of these as well as two previously published microsatellite loci were positioned on the existing genetic linkage map of M. graminicola on 13 of the 24 linkage groups. Most (66%) of the primer pairs also amplified bands in the closely related barley pathogen Septoria passerinii, but only six were polymorphic among four isolates tested. A subset of the primer pairs also revealed polymorphisms when tested with DNA from the related banana black leaf streak (Black Sigatoka) pathogen, M. fijiensis. The EST database provided an excellent source of new, highly polymorphic microsatellite markers that can be multiplexed for high-throughput genetic analyses of M. graminicola and related species.

Alleles↗
PubMed2024

RNF115 aggravates tumor progression through regulation of CDK10 degradation in thyroid carcinoma.

BACKGROUND: RING Finger Protein 115 (RNF115), a notable E3 ligase, is known to modulate tumorigenesis and metastasis. In our investigation, we endeavor to unravel the putative function and inherent mechanism through which RNF115 influences the evolution of thyroid carcinoma (THCA). METHODS: We analyzed RNF115 expression in THCA using the Cancer Genome Atlas (TCGA) database. The influence of RNF115 on the progression of THCA was evaluated using both in vitro and in vivo experimental approaches. The protein regulated by RNF115 was identified through bioinformatics analysis, and its biological significance was further explored. RESULTS: In both THCA tissues and cells, RNF115 showed elevated expression levels. Enhanced expression of RNF115 fostered cell proliferation, tumor growth, and the exacerbation of epithelial-mesenchymal transition (EMT) in THCA, while also promoting tumor lung metastasis. Bioinformatics analysis identified cyclin-dependent kinase 10 (CDK10) as a downstream target of RNF115, which was found to be ubiquitinated and degraded by RNF115 in THCA cells. Functionally, overexpression of CDK10 was found to counteract the promotion of malignant phenotype in THCA induced by RNF115. From a mechanistic perspective, RNF115 activated the Raf-1 pathway and enhanced cancer cell cycle progression by degrading CDK10 in THCA cells. CONCLUSION: RNF115 triggers cell proliferation, EMT, and tumor metastasis by ubiquitinating and degrading CDK10. The regulation of the Raf-1 pathway and cell cycle progression in THCA may be profoundly influenced by this process.

Humans↗
PubMedDate not supplied

"Plasmo2D": an ancillary proteomic tool to aid identification of proteins from Plasmodium falciparum.

Bioinformatics tools to aid gene and protein sequence analysis have become an integral part of biology in the post-genomic era. Release of the Plasmodium falciparum genome sequence has allowed biologists to define the gene and the predicted protein content as well as their sequences in the parasite. Using pI and molecular weight as characteristics unique to each protein, we have developed a bioinformatics tool to aid identification of proteins from Plasmodium falciparum. The tool makes use of a Virtual 2-DE generated by plotting all of the proteins from the Plasmodium database on a pI versus molecular weight scale. Proteins are identified by comparing the position of migration of desired protein spots from an experimental 2-DE and that on a virtual 2-DE. The procedure has been automated in the form of user-friendly software called "Plasmo2D". The tool can be downloaded from http://144.16.89.25/Plasmo2D.zip.

Animals↗
PubMedDate not supplied

Bioinformatics and genomic medicine.

Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational science. Clinical informatics has long developed methodologies to improve biomedical research and clinical care by integrating experimental and clinical information systems. The informatics revolution in both bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high-throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever, in much the same way that biochemistry did a generation ago. This paper describes how these technologies will impact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics and proteomics. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine-learning algorithms are discussed. Use of integrative biochip informatics technologies, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and the integrated management of biomolecular databases, are also discussed.

Computational Biology↗