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At least 1,423 records · Page 79Linked to original sources
PubMed2026

The bioinformatics approach to identifying pathogenic variants for colorectal cancer (CRC).

Colorectal cancer (CRC) is the third most prevalent cancer globally, accounting for 9.6% of newly diagnosed cases and 9.3% of cancer-related deaths. It develops from the uncontrolled proliferation of glandular cells in the colon and rectum and is categorized into three primary types: sporadic, hereditary, and colitis-associated. While genetic susceptibility is a key factor in CRC pathogenesis, identifying high-impact pathogenic variants remains a significant challenge. This study integrates bioinformatics and population genetics approaches to identify CRC-associated single-nucleotide polymorphisms (SNPs) with potential clinical significance. CRC-associated SNPs were extracted from the Genome-Wide Association Studies (GWAS) Catalog, functionally annotated via HaploReg, and validated via Ensembl. In addition, expression quantitative trait locus (eQTL) data from the GTEx database were used to assess the effects of these variants on gene expression across human tissues. Our analysis identified three high-priority SNPs (rs9379084, rs3184504, and rs11557154) associated with the RREB1, ATXN2, SH2B3, and DCAF12 genes, which exhibited marked allele frequency differences among populations. These findings suggest potential biomarkers for CRC risk assessment and highlight the importance of genetic screening across diverse populations.

Bioinformatics↗
PubMed2000

Using the CATH domain database to assign structures and functions to the genome sequences.

The CATH database of protein structures contains approximately 18000 domains organized according to their (C)lass, (A)rchitecture, (T)opology and (H)omologous superfamily. Relationships between evolutionary related structures (homologues) within the database have been used to test the sensitivity of various sequence search methods in order to identify relatives in Genbank and other sequence databases. Subsequent application of the most sensitive and efficient algorithms, gapped blast and the profile based method, Position Specific Iterated Basic Local Alignment Tool (PSI-BLAST), could be used to assign structural data to between 22 and 36 % of microbial genomes in order to improve functional annotation and enhance understanding of biological mechanism. However, on a cautionary note, an analysis of functional conservation within fold groups and homologous superfamilies in the CATH database, revealed that whilst function was conserved in nearly 55% of enzyme families, function had diverged considerably, in some highly populated families. In these families, functional properties should be inherited far more cautiously and the probable effects of substitutions in key functional residues carefully assessed.

Algorithms↗
PubMed2003

Genome-scale functional profiling of the mammalian AP-1 signaling pathway.

Large-scale functional genomics approaches are fundamental to the characterization of mammalian transcriptomes annotated by genome sequencing projects. Although current high-throughput strategies systematically survey either transcriptional or biochemical networks, analogous genome-scale investigations that analyze gene function in mammalian cells have yet to be fully realized. Through transient overexpression analysis, we describe the parallel interrogation of approximately 20,000 sequence annotated genes in cancer-related signaling pathways. For experimental validation of these genome data, we apply an integrative strategy to characterize previously unreported effectors of activator protein-1 (AP-1) mediated growth and mitogenic response pathways. These studies identify the ADP-ribosylation factor GTPase-activating protein Centaurin alpha1 and a Tudor domain-containing hypothetical protein as putative AP-1 regulatory oncogenes. These results provide insight into the composition of the AP-1 signaling machinery and validate this approach as a tractable platform for genome-wide functional analysis.

Animals↗
PubMed2005

cAMP is a ligand for the tandem GAF domain of human phosphodiesterase 10 and cGMP for the tandem GAF domain of phosphodiesterase 11.

N-terminal tandem GAF domains are present in 5 out of 11 mammalian phosphodiesterase (PDE) families. The ligand for the GAF domains of PDEs 2, 5, and 6 is cGMP, whereas those for PDEs 10 and 11 remained enigmatic for years. Here we used the cyanobacterial cyaB1 adenylyl cyclase, which has an N-terminal tandem GAF domain closely related to those of the mammalian PDEs, as an assay system to identify the ligands for the human PDEs 10 and 11 GAF domains. We report that a chimera between the PDE10 GAF domain and the cyanobacterial cyclase was 9-fold stimulated by cAMP (EC50= 19.8 microm), whereas cGMP had only low activity. cAMP increased Vmax in a non-cooperative manner and did not affect the Km for ATP of 27 microm. In an analogous chimeric construct with the tandem GAF domain of human PDE11A4, cGMP was identified as an allosteric activator (EC50 = 72.5 microm) that increased Vmax of the cyclase non-cooperatively 4-fold. GAF-B of PDE10 and GAF-A of PDE11A4 contain an invariant NKFDE motif present in all mammalian PDE GAF ensembles. We mutated the aspartates within this motif in both regions and found that intramolecular signaling was considerably reduced or abolished. This was in line with all data concerning GAF domains with an NKFDE motif as far as they have been tested. The data appeared to define those GAF domains as a distinct subclass within the >3100 annotated GAF domains for which we propose a tentative classification scheme.

3',5'-Cyclic-GMP Phosphodiesterases↗
PubMed2004

Automatic extraction of gene/protein biological functions from biomedical text.

MOTIVATION: With the rapid advancement of biomedical science and the development of high-throughput analysis methods, the extraction of various types of information from biomedical text has become critical. Since automatic functional annotations of genes are quite useful for interpreting large amounts of high-throughput data efficiently, the demand for automatic extraction of information related to gene functions from text has been increasing. RESULTS: We have developed a method for automatically extracting the biological process functions of genes/protein/families based on Gene Ontology (GO) from text using a shallow parser and sentence structure analysis techniques. When the gene/protein/family names and their functions are described in ACTOR (doer of action) and OBJECT (receiver of action) relationships, the corresponding GO-IDs are assigned to the genes/proteins/families. The gene/protein/family names are recognized using the gene/protein/family name dictionaries developed by our group. To achieve wide recognition of the gene/protein/family functions, we semi-automatically gather functional terms based on GO using co-occurrence, collocation similarities and rule-based techniques. A preliminary experiment demonstrated that our method has an estimated recall of 54-64% with a precision of 91-94% for actually described functions in abstracts. When applied to the PUBMED, it extracted over 190 000 gene-GO relationships and 150 000 family-GO relationships for major eukaryotes.

Abstracting and Indexing↗
PubMed2004

In silico gene function prediction using ontology-based pattern identification.

MOTIVATION: With the emergence of genome-wide expression profiling data sets, the guilt by association (GBA) principle has been a cornerstone for deriving gene functional interpretations in silico. Given the limited success of traditional methods for producing clusters of genes with great amounts of functional similarity, new data-mining algorithms are required to fully exploit the potential of high-throughput genomic approaches. RESULTS: Ontology-based pattern identification (OPI) is a novel data-mining algorithm that systematically identifies expression patterns that best represent existing knowledge of gene function. Instead of relying on a universal threshold of expression similarity to define functionally related groups of genes, OPI finds the optimal analysis settings that yield gene expression patterns and gene lists that best predict gene function using the principle of GBA. We applied OPI to a publicly available gene expression data set on the life cycle of the malarial parasite Plasmodium falciparum and systematically annotated genes for 320 functional categories based on current Gene Ontology annotations. An ontology-based hierarchical tree of the 320 categories provided a systems-wide biological view of this important malarial parasite.

Algorithms↗
PubMed2005

DictyMOLD-a Dictyostelium discoideum genome browser database.

UNLABELLED: With the Dictyostelium Genome Project nearing completion, we initiated the construction of a data repository for all Dictyostelium discoideum genomic data. Up to now this database, called DictyMOLD (Dicty Map Of Linked Data), incorporates the recently completed D.discoideum chromosomes 1 and 2 sequences together with related annotations. To visualise maps, sequences and annotations and to provide access for the scientific community a perl-based browser was developed. AVAILABILITY: The DictyMOLD database is freely accessible via http://genome.imb-jena.de/dictyostelium/ CONTACT: gernot@imb-jena.de.

Animals↗
PubMed2005

REDfly: a Regulatory Element Database for Drosophila.

Bioinformatics studies of transcriptional regulation in the metazoa are significantly hindered by the absence of readily available data on large numbers of transcriptional cis-regulatory modules (CRMs). Even the richly annotated Drosophila melanogaster genome lacks extensive CRM information. We therefore present here a database of Drosophila CRMs curated from the literature complete with both DNA sequence and a searchable description of the gene expression pattern regulated by each CRM. This resource should greatly facilitate the development of computational approaches to CRM discovery as well as bioinformatics analyses of regulatory sequence properties and evolution.

Animals↗
PubMed2006

Integrative Array Analyzer: a software package for analysis of cross-platform and cross-species microarray data.

The rapid accumulation of microarray data translates into an urgent need for tools to perform integrative microarray analysis. Integrative Array Analyzer is a comprehensive analysis and visualization software toolkit, which aims to facilitate the reuse of the large amount of cross-platform and cross-species microarray data. It is composed of the data preprocess module, the co-expression analysis module, the differential expression analysis module, the functional and transcriptional annotation module and the graph visualization module.

Algorithms↗
PubMed2026

Highly Contiguous Is Not Chromosomally Accurate: Integrated Cytogenetic and Genomic Mapping in Two Turtle Genome.

High-quality genome assemblies are essential for robust research across biological and medical fields. Assembly errors can have far-reaching consequences for downstream analyses, including gene annotation and the inference of synteny. In contrast to the rapid growth of genomic data volume, there is a notable lag in the integration of chromosome-level assemblies with cytogenetic data. We conducted the first direct genome-to-genome comparison, integrating comparative chromosome painting, the alignment of chromosome-specific probes to available genome assemblies, and synteny-based comparison of independent chromosome-level assemblies of the loggerhead sea turtle (Caretta caretta, 2n = 56) and the red-eared slider (Trachemys scripta elegans, 2n = 50). Using two independent sets of flow-sorted chromosome-specific probes in cross-species hybridizations, together with the sequencing and mapping of chromosome-derived DNA libraries, we assigned assembled scaffolds to all physical chromosomes of both species. In C. caretta, chromosomal assignments and genome-wide synteny were fully consistent with the published assembly, except for the reduced sizes of two microchromosome scaffolds, which we attribute to under-representation of repetitive DNA. In contrast, in T. s. elegans, cytogenetic validation of the assemblies revealed a false rearrangement compared to a missed one. Our results show that even highly contiguous vertebrate genome assemblies can misrepresent chromosome structure. When cytogenetic analyses reveal such inaccuracies, updated reference genomes should be generated for widely studied species to enable accurate inference of karyotype evolution and downstream comparative genomic analyses.

FISH↗
PubMed2000

CyanoBase, the genome database for Synechocystis sp. strain PCC6803: status for the year 2000.

CyanoBase provides an online resource for access to data on genomic information about the cyanobacterium Synechocystis sp. strain PCC6803. The database contains annotations for each protein-coding gene deduced from the entire nucleotide sequence of the genome, gene classification lists, and keyword and similarity search engines. Core portions of CyanoBase consist of annotations for each of the 3168 protein genes deduced from the entire nucleotide sequence of this genome. The contents of each gene were improved by updating with the results of similarity searches and by introducing references for analysis in bioinformatics. The database now contains repository facilities that store and provide experimental information, in addition to providing proposals for the function of each gene. This information should help to avoid unnecessary, overlapping experiments and should assist communication between scientists who wish to elucidate the function of putative genes on the cyanobacteria genome. The current URL of CyanoBase is http://www.kazusa.or.jp:8080/cyano/

Cyanobacteria↗
PubMed2004

GeneDB: a resource for prokaryotic and eukaryotic organisms.

GeneDB (http://www.genedb.org/) is a genome database for prokaryotic and eukaryotic organisms. The resource provides a portal through which data generated by the Pathogen Sequencing Unit at the Wellcome Trust Sanger Institute and other collaborating sequencing centres can be made publicly available. It combines data from finished and ongoing genome and expressed sequence tag (EST) projects with curated annotation, that can be searched, sorted and downloaded, using a single web based resource. The current release stores 11 datasets of which six are curated and maintained by biologists, who review and incorporate information from the scientific literature, public databases and the respective research communities.

Animals↗
PubMed2004

CADRE: the Central Aspergillus Data REpository.

CADRE is a public resource for housing and analysing genomic data extracted from species of Aspergillus. It arose to enable maintenance of the complete annotated genomic sequence of Aspergillus fumigatus and to provide tools for searching, analysing and visualizing features of fungal genomes. By implementing CADRE using Ensembl, a framework is in place for storing and comparing several genomes: the resource will thus expand by including other Aspergillus genomes (such as Aspergillus nidulans) as they become available. CADRE is accessible at http://www.cadre. man.ac.uk.

Aspergillus↗
PubMed2004

HOMSTRAD: recent developments of the Homologous Protein Structure Alignment Database.

HOMSTRAD (http://www-cryst.bioc.cam.ac.uk/ homstrad/) is a collection of protein families, clustered on the basis of sequence and structural similarity. The database is unique in that the protein family sequence alignments have been specially annotated using the program, JOY, to highlight a wide range of structural features. Such data are useful for identifying key structurally conserved residues within the families. Superpositions of the structures within each family are also available and a sensitive structure-aided search engine, FUGUE, can be used to search the database for matches to a query protein sequence. Historically, HOMSTRAD families were generated using several key pieces of software, including COMPARER and MNYFIT, and held in a number of flat files and indexes. A new relational database version of HOMSTRAD, HOMSTRAD BETA (http://www-cryst.bioc.cam. ac.uk/homstradbeta/) is being developed using MySQL. This relational data structure provides more flexibility for future developments, reduces update times and makes data more easily accessible. Consequently it has been possible to add a number of new web features including a custom alignment facility. Altogether, this makes HOMSTRAD and its new BETA version, an excellent resource both for comparative modelling and for identifying distant sequence/structure similarities between proteins.

Amino Acid Sequence↗
PubMed2005

The Mouse Genome Database (MGD): from genes to mice--a community resource for mouse biology.

The Mouse Genome Database (MGD) forms the core of the Mouse Genome Informatics (MGI) system (http://www.informatics.jax.org), a model organism database resource for the laboratory mouse. MGD provides essential integration of experimental knowledge for the mouse system with information annotated from both literature and online sources. MGD curates and presents consensus and experimental data representations of genotype (sequence) through phenotype information, including highly detailed reports about genes and gene products. Primary foci of integration are through representations of relationships among genes, sequences and phenotypes. MGD collaborates with other bioinformatics groups to curate a definitive set of information about the laboratory mouse and to build and implement the data and semantic standards that are essential for comparative genome analysis. Recent improvements in MGD discussed here include the enhancement of phenotype resources, the re-development of the International Mouse Strain Resource, IMSR, the update of mammalian orthology datasets and the electronic publication of classic books in mouse genetics.

Animals↗
PubMed2006

metaSHARK: a WWW platform for interactive exploration of metabolic networks.

The metaSHARK (metabolic search and reconstruction kit) web server offers users an intuitive, fully interactive way to explore the KEGG metabolic network via a WWW browser. Metabolic reconstruction information for specific organisms, produced by our automated SHARKhunt tool or from other programs or genome annotations, may be uploaded to the website and overlaid on the generic network. Additional data from gene expression experiments can also be incorporated, allowing the visualization of differential gene expression in the context of the predicted metabolic network. metaSHARK is available at http://bioinformatics.leeds.ac.uk/shark/.

Animals↗
PubMed2000

The CATH Dictionary of Homologous Superfamilies (DHS): a consensus approach for identifying distant structural homologues.

A consensus approach has been developed for identifying distant structural homologues. This is based on the CATH Dictionary of Homologous Superfamilies (DHS), a database of validated multiple structural alignments annotated with consensus functional information for evolutionary protein superfamilies (URL: http://www. biochem.ucl.ac.uk/bsm/dhs). Multiple structural alignments have been generated for 362 well-populated superfamilies in the CATH structural domain database and annotated with secondary structure, physicochemical properties, functional sequence patterns and protein-ligand interaction data. Consensus functional information for each superfamily includes descriptions and keywords extracted from SWISS-PROT and the ENZYME database. The Dictionary provides a powerful resource to validate, examine and visualize key structural and functional features of each homologous superfamily. The value of the DHS, for assessing functional variability and identifying distant evolutionary relationships, is illustrated using the pyridoxal-5'-phosphate (PLP) binding aspartate aminotransferase superfamily. The DHS also provides a tool for examining sequence-structure relationships for proteins within each fold group.

Amino Acid Sequence↗
PubMed2025

ClarID: A Human-Readable and Compact Identifier Specification for Biomedical Metadata Integration.

BACKGROUND: In biomedical research, subjects and biospecimens are commonly tracked using simple IDs or UUIDs, which guarantee uniqueness but convey no embedded semantic information. Contextual metadata (such as tissue type, diagnosis, or assay) is often stored separately, making integration, cohort selection, and downstream analysis cumbersome. While structured barcoding systems exist in large consortia (e.g., TCGA, GTEx) or domain-specific contexts (e.g., SPREC, GOLD), no unified, extensible framework currently spans both subjects and biosamples in a human- and machine-readable way. METHODS: We developed ClarID, a domain-agnostic specification that supports two identifier formats: (i) a human-readable form (e.g., 'CNAG_Test-HomSap-00001-LIV-TUM-RNA-C22.0-TRT-P1W' that encodes key metadata such as project, species, subject_id, tissue, assay, disease, timepoint and duration (from that event); and (ii) a compact version named 'stub' (e.g., 'CT01001LTR0N401T1W') optimized for filenames, pipelines, and labeling.ClarID is implemented through an open-source command-line tool, ClarID-Tools, which processes tabular metadata files (CSV/TSV) and uses a YAML-based codebook to generate, decode, and validate identifiers, as well as to create and read QR codes. The tool supports bulk and single-sample processing and allows easy integration with institutional workflows. RESULTS: To demonstrate ClarID's utility, we applied it to datasets from the Genomic Data Commons (GDC), generating interpretable identifiers for more than 113,000 clinical records (subjects) and 4,255 biospecimen records. All materials, including pre-processing scripts, input and encoded data, are publicly available and fully reproducible via the accompanying GitHub repository and Google Colab. CONCLUSIONS: ClarID fills a critical gap between opaque accession numbers and rich metadata schemas by embedding key context directly into structured identifiers. It enhances traceability, facilitates downstream analysis, and remains adaptable to project-specific needs through a configurable codebook. The accompanying ClarID-Tools software is freely available, together with full documentation and reproducible pipelines, at https://github.com/CNAG-Biomedical-Informatics/clarid-tools.

Biosample identifiers↗