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At least 811 records · Page 45Linked to original sources

MeKE: discovering the functions of gene products from biomedical literature via sentence alignment.

MOTIVATION: Research on roles of gene products in cells is accumulating and changing rapidly, but most of the results are still reported in text form and are not directly accessible by computers. To expedite the progress of functional bioinformatics, it is, therefore, important to efficiently process large amounts of biomedical literature and transform the knowledge extracted into a structured format usable by biologists and medical researchers. Our aim was to develop an intelligent text-mining system that will extract from biomedical documents knowledge about the functions of gene products and thus facilitate computing with function. RESULTS: We have developed an ontology-based text-mining system to efficiently extract from biomedical literature knowledge about the functions of gene products. We also propose methods of sentence alignment and sentence classification to discover the functions of gene products discussed in digital texts. AVAILABILITY: http://ismp.csie.ncku.edu.tw/~yuhc/meke/

Biomedical Research↗

The RCSB Protein Data Bank: a redesigned query system and relational database based on the mmCIF schema.

The Protein Data Bank (PDB) is the central worldwide repository for three-dimensional (3D) structure data of biological macromolecules. The Research Collaboratory for Structural Bioinformatics (RCSB) has completely redesigned its resource for the distribution and query of 3D structure data. The re-engineered site is currently in public beta test at http://pdbbeta.rcsb.org. The new site expands the functionality of the existing site by providing structure data in greater detail and uniformity, improved query and enhanced analysis tools. A new key feature is the integration and searchability of data from over 20 other sources covering genomic, proteomic and disease relationships. The current capabilities of the re-engineered site, which will become the RCSB production site at http://www.pdb.org in late 2005, are described.

Databases, Protein↗

DBCollHIV: a database system for collaborative HIV analysis in Brazil.

We developed a database system for collaborative HIV analysis (DBCollHIV) in Brazil. The main purpose of our DBCollHIV project was to develop an HIV-integrated database system with analytical bioinformatics tools that would support the needs of Brazilian research groups for data storage and sequence analysis. Whenever authorized by the principal investigator, this system also allows the integration of data from different studies and/or the release of the data to the general public. The development of a database that combines sequences associated with clinical/epidemiological data is difficult without the active support of interdisciplinary investigators. A functional database that securely stores data and helps the investigator to manipulate their sequences before publication would be an attractive tool for investigators depositing their data and collaborating with other groups. DBCollHIV allows investigators to manipulate their own datasets, as well as integrating molecular and clinical HIV data, in an innovative fashion.

Brazil↗

Exploring the pathway structure of metabolism: decomposition into subnetworks and application to Mycoplasma pneumoniae.

MOTIVATION: Reconstructing and analyzing the metabolic map of microorganisms is an important challenge in bioinformatics. Pathway analysis of large metabolic networks meets with the problem of combinatorial explosion of pathways. Therefore, appropriate algorithms for an automated decomposition of these networks into smaller subsystems are needed. RESULTS: A decomposition algorithm for metabolic networks based on the local connectivity of metabolites is presented. Interrelations of this algorithm with alternative methods proposed in the literature and the theory of small world networks are discussed. The applicability of our method is illustrated by an analysis of the metabolism of Mycoplasma pneumoniae, which is an organism of considerable medical interest. The decomposition gives rise to 19 subnetworks. Three of these are here discussed in biochemical terms: arginine degradation, the tetrahydrofolate system, and nucleotide metabolism. The interrelations of pathway analysis of biochemical networks with Petri net theory are outlined.

Algorithms↗

ORCO: Ollivier-Ricci Curvature-Omics-an unsupervised method for analyzing robustness in biological systems.

MOTIVATION: Although recent advanced sequencing technologies have improved the resolution of genomic and proteomic data to better characterize molecular phenotypes, efficient computational tools to analyze and interpret large-scale omic data are still needed. RESULTS: To address this, we have developed a network-based bioinformatic tool called Ollivier-Ricci curvature for omics (ORCO). ORCO incorporates omics data and a network describing biological relationships between the genes or proteins and computes Ollivier-Ricci curvature (ORC) values for individual interactions. ORC is an edge-based measure that assesses network robustness. It captures functional cooperation in gene signaling using a consistent information-passing measure, which can help investigators identify therapeutic targets and key regulatory modules in biological systems. ORC has identified novel insights in multiple cancer types using genomic data and in neurodevelopmental disorders using brain imaging data. This tool is applicable to any data that can be represented as a network. AVAILABILITY AND IMPLEMENTATION: ORCO is an open-source Python package and is publicly available on GitHub at https://github.com/aksimhal/ORC-Omics.

Software↗

Stubb: a program for discovery and analysis of cis-regulatory modules.

Given the DNA-binding specificities (motifs) of one or more transcription factors, an important bioinformatics problem is to discover significant clusters of binding sites for the transcription factors(s). Such clusters often correspond to cis-regulatory modules mediating regulation of an adjacent gene. In earlier work, we developed the Stubb program that uses a probabilistic model and a maximum likelihood approach to efficiently detect cis-regulatory modules over genomic scales. It may optionally exploit a second related genome to improve module prediction accuracy. We describe here the use of a web-based interface for the Stubb program. The interface is equipped with a special post-processing step for in-depth analysis of specific modules, in order to reveal individual binding sites predicted in the module. The web server may be accessed at the URL http://stubb.rockefeller.edu/.

Algorithms↗

An inquiry into protein structure and genetic disease: introducing undergraduates to bioinformatics in a large introductory course.

This inquiry-based lab is designed around genetic diseases with a focus on protein structure and function. To allow students to work on their own investigatory projects, 10 projects on 10 different proteins were developed. Students are grouped in sections of 20 and work in pairs on each of the projects. To begin their investigation, students are given a cDNA sequence that translates into a human protein with a single mutation. Each case results in a genetic disease that has been studied and recorded in the Online Mendelian Inheritance in Man (OMIM) database. Students use bioinformatics tools to investigate their proteins and form a hypothesis for the effect of the mutation on protein function. They are also asked to predict the impact of the mutation on human physiology and present their findings in the form of an oral report. Over five laboratory sessions, students use tools on the National Center for Biotechnology Information (NCBI) Web site (BLAST, LocusLink, OMIM, GenBank, and PubMed) as well as ExPasy, Protein Data Bank, ClustalW, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and the structure-viewing program DeepView. Assessment results showed that students gained an understanding of the Web-based databases and tools and enjoyed the investigatory nature of the lab.

Algorithms↗

BASC: an integrated bioinformatics system for Brassica research.

The BASC system provides tools for the integrated mining and browsing of genetic, genomic and phenotypic data. This public resource hosts information on Brassica species supporting the Multinational Brassica Genome Sequencing Project, and is based upon five distinct modules, ESTDB, Microarray, MarkerQTL, CMap and EnsEMBL. ESTDB hosts expressed gene sequences and related annotation derived from comparison with GenBank, UniRef and the genome sequence of Arabidopsis. The Microarray module hosts gene expression information related to genes annotated within ESTDB. MarkerQTL is the most complex module and integrates information on genetic markers, maps, individuals, genotypes and traits. Two further modules include an Arabidopsis EnsEMBL genome viewer and the CMap comparative genetic map viewer for the visualization and integration of genetic and genomic data. The database is accessible at http://bioinformatics.pbcbasc.latrobe.edu.au.

Arabidopsis↗

TriosCompass: a snakemake workflow for integrated detection of SNVs, indels, STRs, and structural de novo variants in parent-child trios.

MOTIVATION: The accurate and sensitive identification of de novo variants, which are unique to an individual and not found in the parents' germlines, is critical for understanding the genetic basis of rare diseases, developmental disorders, and evolutionary processes. Existing de novo variant detection pipelines often lack the flexibility to handle multiple variant types, struggle with speed and reproducibility across computational environments, demand extensive manual configuration, or require bioinformatics expertise for downstream curation and analysis, limiting their scalability and usability for large genomic studies. Accordingly, there is a pressing need to better address these challenges. RESULTS: We introduce TriosCompass, an open-source Snakemake workflow that addresses these challenges by providing a modular, accelerated, and environmentally-configurable end-to-end solution for comprehensive de novo variant discovery. It integrates state-of-the-art tools into a reproducible framework, empowering researchers to discover novel genetic insights with greater efficiency and reliability. AVAILABILITY: TriosCompass is implemented as a Snakemake workflow and is freely available at https://github.com/NCI-CGR/TriosCompass_v2 or on Zenodo (10.5281/zenodo.17981062). SUPPLEMENTARY INFORMATION: Supplementary data is available on GitHub at https://github.com/NCI-CGR/TriosCompass_v2/tree/manuscript/report_dashboards. Supplementary methods on DeepTrio benchmark runs can be viewed at: https://github.com/NCI-CGR/TriosCompass_v2/blob/manuscript/TriosCompass_Supp_Methods_deeptrio_benchmark.md.

Software↗

FAST DB: a website resource for the study of the expression regulation of human gene products.

Human genes use various mechanisms to generate different transcripts having different exon content, which in turn generate multiple protein isoforms having differential and even opposite biological activities. To understand the biological consequences of gene transcriptional activity modulation, it is necessary to integrate the capability of genes to generate distinct functional products, particularly because transcriptional stimuli also affect the exon content of their target gene products. For this purpose, we have developed a bioinformatics suite, FAST DB, which defines easily and accurately the exon content of all known transcripts produced by human genes. In addition, several tools have been developed, including a graphical presentation of all gene products, a sequence multi-alignment of all gene transcripts and an in silico PCR computer program. The FAST DB interface also offers extensive links to website resources for promoter analysis and transcription factor binding site prediction, splicing regulatory sequence prediction, as well as 5'- and 3'-untranslated region analysis. FAST DB has been designed to facilitate studies that integrate transcriptional and post-transcriptional events to investigate the expression regulation of human gene products.

Alternative Splicing↗

E-MSD: the European Bioinformatics Institute Macromolecular Structure Database.

The E-MSD macromolecular structure relational database (http://www.ebi.ac.uk/msd) is designed to be a single access point for protein and nucleic acid structures and related information. The database is derived from Protein Data Bank (PDB) entries. Relational database technologies are used in a comprehensive cleaning procedure to ensure data uniformity across the whole archive. The search database contains an extensive set of derived properties, goodness-of-fit indicators, and links to other EBI databases including InterPro, GO, and SWISS-PROT, together with links to SCOP, CATH, PFAM and PROSITE. A generic search interface is available, coupled with a fast secondary structure domain search tool.

Animals↗

PathoSeq-QC: a decision support bioinformatics workflow for robust genomic surveillance.

MOTIVATION: Recommendations on the use of genomics for pathogens surveillance are evidence that high-throughput genomic sequencing plays a key role to fight global health threats. Coupled with bioinformatics and other data types (e.g., epidemiological information), genomics is used to obtain knowledge on health pathogenic threats and insights on their evolution, to monitor pathogens spread, and to evaluate the effectiveness of countermeasures. From a decision-making policy perspective, it is essential to ensure the entire process's quality before relying on analysis results as evidence. Available workflows usually offer quality assessment tools that are primarily focused on the quality of raw NGS reads but often struggle to keep pace with new technologies and threats, and fail to provide a robust consensus on results, necessitating manual evaluation of multiple tool outputs. RESULTS: We present PathoSeq-QC, a bioinformatics decision support workflow developed to improve the trustworthiness of genomic surveillance analyses and conclusions. Designed for SARS-CoV-2, it is suitable for any viral threat. In the specific case of SARS-CoV-2, PathoSeq-QC: (i) evaluates the quality of the raw data; (ii) assesses whether the analysed sample is composed by single or multiple lineages; (iii) produces robust variant calling results via multi-tool comparison; (iv) reports whether the produced data are in support of a recombinant virus, a novel or an already known lineage. The tool is modular, which will allow easy functionalities extension. AVAILABILITY AND IMPLEMENTATION: PathoSeq-QC is a command-line tool written in Python and R. The code is available at https://code.europa.eu/dighealth/pathoseq-qc.

Genomics↗

pTARGET: a web server for predicting protein subcellular localization.

The pTARGET web server enables prediction of nine distinct protein subcellular localizations in eukaryotic non-plant species. Predictions are made using a new algorithm [C. Guda and S. Subramaniam (2005) pTARGET [corrected] a new method for predicting protein subcellular localization in eukaryotes. Bioinformatics, 21, 3963-3969], which is primarily based on the occurrence patterns of location-specific protein functional domains in different subcellular locations. We have implemented a relational database, PreCalcDB, to store pre-computed prediction results for all eukaryotic non-plant protein sequences in the public domain that includes about 770,000 entries. Queries can be made by entering protein sequences or by uploading a file containing up to 5000 protein sequences in FASTA format. Prediction results for queries with matching entries in the PreCalcDB will be retrieved instantly; while for the missing ones new predictions will be computed and sent by email. Pre-computed predictions can also be downloaded for complete proteomes of Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila, Mus musculus and Homo sapiens. The server, its documentation and the data are accessible from http://bioinformatics.albany.edu/~ptarget.

Algorithms↗

[A turning point in the knowledge of the structure-function-activity relations of elastin].

In this review are presented the last new results of our research group dealing with the molecular structures (atomic level) of tropoelastin, elastin and elastin derived peptides studied by using essentially methods of bioinformatics (theoretical predictions and molecular modelling) linked to experimental circular dichroism spectroscopic studies. We already had characterized both the local secondary structure and some parts of the tertiary structure of the tropoelastin and elastin molecules (human, bovine...), by using either theoretical predictions (local secondary structure, linear epitopes...) and/or experimental data (optical spectroscopic methods: Raman scattering, infrared absorption, circular dichroism). Except the cross-linking regions which are in helical conformations, the whole tropoelastin structure displays a lot of beta-reverse turns which usually belong to irregular structures in proteins. These turns play a key role in other regularly structures orientation (alpha-helix, beta-strand), thus they are very important in the native protein 3D architecture. It is particularly true for human tropoelastin, because its sequence is rich in glycines and prolines, and these residues are frequently met in beta-turns (a beta-turn is made of four consecutive residues which are stabilized by an hydrogen bond). Several types of beta-turns can be defined with the dihedral angles values phi and psi of the two central residues. Thus, by using a very recent updated set of propensities for the amino acid residues to belong to given types of reverse beta-turns (extracted from a reference set of known 3-D structures of globular proteins), we have determined, (by using our home made software COUDES), for all possible tetrapeptides of the human tropoelastin sequence, the distribution and the characterization of the possible type of turns. Thus, it is shown that the locations and/or the types of these reverse beta-turns reveal a regularity and are not all random. This confirms our hypothesis that intra-molecular elasticity of tropoelastin could be explained by the possibility of transitions between conformations involving short beta-strands and beta-turns. This result is of great interest in the construction (by using molecular biology) of elastic biomaterials derived from the elastin sequence (particularly, the elastin derived peptides corresponding to the sequence exon 21--(exon 24--exon 24...). Our study permit also to predict the conformations of specific elastin derived peptides which could have interesting biological activity. Peptides resulting from the degradation of elastin, the insoluble polymer of tropoelastin and responsible for the elasticity of vertebrate tissues, can induce biological effects and notably the regulation of matrix metalloproteinases (MMP-s) activity. Recently, it was proposed that some elastin derived hexapeptides resulting from circular permutations of VGVAPG (a three fold repetition sequence in exon 24 of human tropoelastin) possess MMP-1 production and activation regulation properties. This effect depends on the presence of the tropoelastin specific membraneous receptor 67 KDa EBP (Elastin Binding Protein). Our results obtained by using both circular dichroism spectroscopy and linear predictions confirmed the hypothesis of a structure dependent mechanism with a possibly occurring type VIII beta-turn on the first four residues of the GXXPG sequence consensus which is only present among all active peptides. Thus, we have performed extensive molecular dynamics studies, in both implicit and explicit solvent, on these active and inactive elastin derived hexapeptides. Using our own analysis method of pattern recognition of the types of the beta-reverse-turns followed during the molecular dynamics trajectory, we found that active and inactive peptides effectively form two well distinct conformational groups in which active peptides preferentially adopt conformation close to type VIII GXXP (beta-reverse-turn. The structural role of the C terminal G residue could also be explained. Additional molecular simulations on (VGVAPG)2 and (VGVAPG)3 show the formation of two or three GXXP tetrapeptides adopting a structure close to type VIII beta-reverse-turn, suggesting a local conformational preference for this motif. This observation of a specific structural single and/or repeated motif is in agreement with the circular dichroism spectra of the involved (VGVAPG)1, (VGVAPG)2 and (VGVAPG)3 peptides and then it can be proposed that their biological activities have to be linear. The final aim of this type of work is to understand more about the sequence/structure/function/activity relationships of those structured peptides in order to propose specific sequences (corresponding to specific structures) for best biological activity results.

Amino Acid Sequence↗

A systematic approach to dynamic programming in bioinformatics.

MOTIVATION: Dynamic programming is probably the most popular programming method in bioinformatics. Sequence comparison, gene recognition, RNA structure prediction and hundreds of other problems are solved by ever new variants of dynamic programming. Currently, the development of a successful dynamic programming algorithm is a matter of experience, talent and luck. The typical matrix recurrence relations that make up a dynamic programming algorithm are intricate to construct, and difficult to implement reliably. No general problem independent guidance is available. RESULTS: This article introduces a systematic method for constructing dynamic programming solutions to problems in biosequence analysis. By a conceptual splitting of the algorithm into a recognition and an evaluation phase, algorithm development is simplified considerably, and correct recurrences can be derived systematically. Without additional effort, the method produces an early, executable prototype expressed in a functional programming language. The method is quite generally applicable, and, while programming effort decreases, no overhead in terms of ultimate program efficiency is incurred.

Algorithms↗

The web server of IBM's Bioinformatics and Pattern Discovery group.

We herein present and discuss the services and content which are available on the web server of IBM's Bioinformatics and Pattern Discovery group. The server is operational around the clock and provides access to a variety of methods that have been published by the group's members and collaborators. The available tools correspond to applications ranging from the discovery of patterns in streams of events and the computation of multiple sequence alignments, to the discovery of genes in nucleic acid sequences and the interactive annotation of amino acid sequences. Additionally, annotations for more than 70 archaeal, bacterial, eukaryotic and viral genomes are available on-line and can be searched interactively. The tools and code bundles can be accessed beginning at http://cbcsrv.watson.ibm.com/Tspd.html whereas the genomics annotations are available at http://cbcsrv.watson.ibm.com/Annotations/.

Computational Biology↗

RACE: Remote Analysis Computation for gene Expression data.

The Remote Analysis Computation for gene Expression data (RACE) suite is a collection of bioinformatics web tools designed for the analysis of DNA microarray data. RACE performs probe-level data preprocessing, extensive quality checks, data visualization and data normalization for Affymetrix GeneChips. In addition, it offers differential expression analysis on normalized expression levels from any array platform. RACE estimates the false discovery rates of lists of potentially regulated genes and provides a Gene Ontology-term analysis tool for GeneChip data to support the biological interpretation and annotation of results. The analysis is fully automated but can be customized by flexible parameter settings. To offer a convenient starting point for subsequent analyses, and to provide maximum transparency, the R scripts used to generate the results can be downloaded along with the output files. RACE is freely available for use at http://race.unil.ch.

Computational Biology↗

Application of parameter optimization to molecular comparison problems.

Various bioinformatics comparison problems require optimizing several different properties simultaneously. Often linear objective functions combine the values for different properties of solution candidates into a single score to allow for multivariate optimization. In this context, an essential question is how each property should be weighted. Frequently, no apparent measure is available to serve as a model for the score. However, if preferences of certain solution candidates over others in a training set are available, the implied partial ordering may be used to best possibly adjust the weights. We apply different strategies to optimize the parameterization of empirical scoring functions used for two molecular comparison problems, protein threading and small molecule superposition. Using well established evaluation methods, it can be shown that the results of both comparison methods are significantly improved by systematically choosing appropriate weights for the scoring function contributions.

Algorithms↗