Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “protein function annotation”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,765 records · Page 98Linked to original sources
PubMed2004

Development of an integrated genome informatics, data management and workflow infrastructure: a toolbox for the study of complex disease genetics.

The genetic dissection of complex disease remains a significant challenge. Sample-tracking and the recording, processing and storage of high-throughput laboratory data with public domain data, require integration of databases, genome informatics and genetic analyses in an easily updated and scaleable format. To find genes involved in multifactorial diseases such as type 1 diabetes (T1D), chromosome regions are defined based on functional candidate gene content, linkage information from humans and animal model mapping information. For each region, genomic information is extracted from Ensembl, converted and loaded into ACeDB for manual gene annotation. Homology information is examined using ACeDB tools and the gene structure verified. Manually curated genes are extracted from ACeDB and read into the feature database, which holds relevant local genomic feature data and an audit trail of laboratory investigations. Public domain information, manually curated genes, polymorphisms, primers, linkage and association analyses, with links to our genotyping database, are shown in Gbrowse. This system scales to include genetic, statistical, quality control (QC) and biological data such as expression analyses of RNA or protein, all linked from a genomics integrative display. Our system is applicable to any genetic study of complex disease, of either large or small scale.

Animals↗
PubMed1997

Of genomes and proteomes.

The era of complete genome sequences has arrived and with it vast amounts of data which must be annotated, cross referenced, and placed within the regulatory networks which define the physiology of an organism. One eucaryotic and three procaryotic genomes have been completed and the data made available and another 50 sequences are expected to be completed by the end of the decade. One of the first steps in the new post genome era will be to decipher the functions of the huge numbers of new open reading frames. Various approaches to investigate what unknown genes do and how genes interact together within an organism are being undertaken, including (1) the simultaneous measurement of the expression levels of all genes in a cell and (2) the mapping and quantitation of all proteins expressed within a cell. The idea of systematically mapping and identifying the total protein complement of the genome (the "proteome") arose over 20 years ago when the separation of proteins from total cell extracts by two dimensional (2D) gel electrophoresis was developed. This review will focus on the use of 2D gel electrophoresis as the basis for constructing proteome maps and on the rapid advances in mass spectrometry which will allow the large-scale, automated identification of proteins which is necessary for the creation of such databases.

Animals↗
PubMed2004

A fuzzy guided genetic algorithm for operon prediction.

MOTIVATION: The operon structure of the prokaryotic genome is a critical input for the reconstruction of regulatory networks at the whole genome level. As experimental methods for the detection of operons are difficult and time-consuming, efforts are being put into developing computational methods that can use available biological information to predict operons. METHOD: A genetic algorithm is developed to evolve a starting population of putative operon maps of the genome into progressively better predictions. Fuzzy scoring functions based on multiple criteria are used for assessing the 'fitness' of the newly evolved operon maps and guiding their evolution. RESULTS: The algorithm organizes the whole genome into operons. The fuzzy guided genetic algorithm-based approach makes it possible to use diverse biological information like genome sequence data, functional annotations and conservation across multiple genomes, to guide the organization process. This approach does not require any prior training with experimental operons. The predictions from this algorithm for Escherchia coli K12 and Bacillus subtilis are evaluated against experimentally discovered operons for these organisms. The accuracy of the method is evaluated using an ROC (receiver operating characteristic) analysis. The area under the ROC curve is around 0.9, which indicates excellent accuracy. CONTACT: roschen_csir@rediffmail.com.

Algorithms↗
PubMed2002

PipeOnline 2.0: automated EST processing and functional data sorting.

Expressed sequence tags (ESTs) are generated and deposited in the public domain, as redundant, unannotated, single-pass reactions, with virtually no biological content. PipeOnline automatically analyses and transforms large collections of raw DNA-sequence data from chromatograms or FASTA files by calling the quality of bases, screening and removing vector sequences, assembling and rewriting consensus sequences of redundant input files into a unigene EST data set and finally through translation, amino acid sequence similarity searches, annotation of public databases and functional data. PipeOnline generates an annotated database, retaining the processed unigene sequence, clone/file history, alignments with similar sequences, and proposed functional classification, if available. Functional annotation is automatic and based on a novel method that relies on homology of amino acid sequence multiplicity within GenBank records. Records are examined through a function ordered browser or keyword queries with automated export of results. PipeOnline offers customization for individual projects (MyPipeOnline), automated updating and alert service. PipeOnline is available at http://stress-genomics.org.

Automation↗
PubMed2025

Identification and classification of ion-channels across the tree of life provide functional insights into understudied CALHM channels.

The ion channel (IC) genes encoded in the human genome play fundamental roles in cellular functions and disease and are one of the largest classes of druggable proteins. However, limited knowledge of the diverse molecular and cellular functions carried out by ICs presents a major bottleneck in developing selective chemical probes for modulating their functions in disease states. The wealth of sequence data available on ICs from diverse organisms provides a valuable source of untapped information for illuminating the unique modes of channel regulation and functional specialization. However, the extensive diversification of IC sequences and the lack of a unified resource present a challenge in effectively using existing data for IC research. Here, we perform integrative mining of available sequence, structure, and functional data on 419 human ICs across disparate sources, including extensive literature mining by leveraging advances in large language models to annotate and curate the full complement of the "channelome". We employ a well-established orthology inference approach to identify and extend the IC orthologs across diverse organisms to above 48,000. We show that the depth of conservation and taxonomic representation of IC sequences can further be translated to functional similarities by clustering them into functionally relevant groups, which can be used for downstream functional prediction on understudied members. We demonstrate this by delineating co-conserved patterns characteristic of the understudied family of the Calcium Homeostasis Modulator (CALHM) family of ICs. Through mutational analysis of co-conserved residues altered in human diseases and electrophysiological studies, we show that these evolutionarily-constrained residues play an important role in channel gating functions. Thus, by providing new tools and resources for performing large comparative analyses on ICs, this study addresses the unique needs of the IC community and provides the groundwork for accelerating the functional characterization of dark channels for therapeutic intervention.

CALHM1↗
PubMed2006

Large-scale correlation of DNA accession numbers to the cDNAs in the FANTOM full-length mouse cDNA clone set.

Oligonucleotide-based microarrays, such as GeneChip, are widely used to determine the large-scale gene expression profiles. However, GeneChip only provides information on the identity of the molecules, and the investigator must obtain each cDNA clone for further analyses. In this study, we devised a program which enables us to correlate a large number of DNA accession numbers to the FANTOM (functional annotation of the mouse) full-length mouse cDNA clone set, and made a correlative table between mouse GeneChip clones and FANTOM clones. This allows easy identification of the corresponding FANTOM clone for each GeneChip clone, even if the sequence of the GeneChip clone does not directly match the FANTOM clone. Using this table, for example, a large number of in situ hybridization probes can be synthesized easily, because the FANTOM clones are flanked by T3/T7 promoters on both ends. In addition, we further developed a program which retrieves the amino acid sequence (AA Seq) for each clone, even for the FANTOM clones that lack the AA Seq description, and classifies the proteins automatically. As an example, we devised a correlation table with predictions of the secretory or transmembrane molecules. The correlation table is useful for a large-scale screening of molecules involved in cell-cell communication in various biological processes. The full correlation table for the GeneChip clones is available at http://www.kjm.keio.ac.jp/past/55/3/correlation_table1.html.

Animals↗
PubMed2003

In silico study of breast cancer associated gene 3 using LION Target Engine and other tools.

Sequence analysis of individual targets is an important step in annotation and validation. As a test case, we investigated human breast cancer associated gene 3 (BCA3) with LION Target Engine and with other bioinformatics tools. LION Target Engine confirmed that the BCA3 gene is located on 11p15.4 and that the two most likely splice variants (lacking exon 3 and exons 3 and 5, respectively) exist. Based on our manual curation of sequence data, it is proposed that an additional variant (missing only exon 5) published in a public sequence repository, is a prediction artifact. A significant number of new orthologs were also identified, and these were the basis for a high-quality protein secondary structure prediction. Moreover, our research confirmed several distinct functional domains as described in earlier reports. Sequence conservation from multiple sequence alignments, splice variant identification, secondary structure predictions, and predicted phosphorylation sites suggest that the removal of interaction sites through alternative splicing might play a modulatory role in BCA3. This in silico approach shows the depth and relevance of an analysis that can be accomplished by including a variety of publicly available tools with an integrated and customizable life science informatics platform.

Adaptor Proteins, Signal Transducing↗
PubMed1999

ProClass Protein Family Database.

ProClass is a protein family database that organizes non-redundant sequence entries into families defined collectively by PROSITE patterns and PIR superfamilies. By combining global similarities and functional motifs into a single classification scheme, ProClass helps to reveal domain and family relationships and classify multi-domain proteins. The database currently consists of more than 120 000 sequence entries, approximately 60% of which is classified into about 3500 families. To maximize family information retrieval, the database provides links to various protein family/domain and structural class databases and contains multiple motif alignments of all PROSITE patterns as well as global alignments of PIR superfamilies. The motif sequences are retrieved from both PIR-International and SWISS-PROT databases, including a large number of new members detected by our GeneFIND family identification system. ProClass can be used to support full-scale genomic annotation, because of its high classification rate. The ProClass database is available for on-line search and record retrieval from our WWW server at http://diana.uthct.edu/proclass.html

Amino Acid Sequence↗
PubMed2000

The 1999 SWISS-2DPAGE database update.

SWISS-2DPAGE (http://www.expasy.ch/ch2d/ ) is an annotated two-dimensional polyacrylamide gel electro-phoresis (2-DE) database established in 1993. The current release contains 24 reference maps from human and mouse biological samples, as well as from Saccharomyces cerevisiae, Escherichia coli and Dictyostelium discoideum origin. These reference maps have now 2824 identified spots, corresponding to 614 separate protein entries in the database, in addition to virtual entries for each SWISS-PROT sequence or any user-entered amino acids sequence. Last year improvements in the SWISS-2DPAGE database are as follows: three new maps have been created and several others have been updated; cross-references to newly built federated 2-DE databases have been added; new functions to access the data have been provided through the ExPASy proteomics server.

Animals↗
PubMed2000

Links from genome proteins to known 3-D structures.

We describe a genome annotation service provided by the Entrez browser, http://www.ncbi.nlm.nih.gov/entrez. All protein products identified in fully sequenced microbial genomes have been compared with proteins with known 3-D structure by use of the BLAST sequence comparison algorithm. For the approximately 20% of genome proteins in which unambiguous sequence similarity is detected, Entrez provides a link from the gene product to its predicted structure. The service uses the Cn3D molecular graphics viewer to present a 3-D view of the known structure, together with an alignment display mapping conserved residues from the genome protein onto the known structure. Using an example from Aeropyrum pernix, we illustrate how mapping to a 3-D structure can confirm predictions of biological function.

Algorithms↗
PubMed1995

The Genexpress Index: a resource for gene discovery and the genic map of the human genome.

Detailed analysis of a set of 18,698 sequences derived from both ends of 10,979 human skeletal muscle and brain cDNA clones defined 6676 functional families, characterized by their sequence signatures over 5750 distinct human gene transcripts. About half of these genes have been assigned to specific chromosomes utilizing 2733 eSTS markers, the polymerase chain reaction, and DNA from human-rodent somatic cell hybrids. Sequence and clone clustering and a functional classification together with comprehensive data base searches and annotations made it possible to develop extensive sequence and map cross-indexes, define electronic expression profiles, identify a new set of overlapping genes, and provide numerous new candidate genes for human pathologies.

Amino Acid Sequence↗
PubMed2006

Detecting overlapping coding sequences in virus genomes.

BACKGROUND: Detecting new coding sequences (CDSs) in viral genomes can be difficult for several reasons. The typically compact genomes often contain a number of overlapping coding and non-coding functional elements, which can result in unusual patterns of codon usage; conservation between related sequences can be difficult to interpret--especially within overlapping genes; and viruses often employ non-canonical translational mechanisms--e.g. frameshifting, stop codon read-through, leaky-scanning and internal ribosome entry sites--which can conceal potentially coding open reading frames (ORFs). RESULTS: In a previous paper we introduced a new statistic--MLOGD (Maximum Likelihood Overlapping Gene Detector)--for detecting and analysing overlapping CDSs. Here we present (a) an improved MLOGD statistic, (b) a greatly extended suite of software using MLOGD, (c) a database of results for 640 virus sequence alignments, and (d) a web-interface to the software and database. Tests show that, from an alignment with just 20 mutations, MLOGD can discriminate non-overlapping CDSs from non-coding ORFs with a typical accuracy of up to 98%, and can detect CDSs overlapping known CDSs with a typical accuracy of 90%. In addition, the software produces a variety of statistics and graphics, useful for analysing an input multiple sequence alignment. CONCLUSION: MLOGD is an easy-to-use tool for virus genome annotation, detecting new CDSs--in particular overlapping or short CDSs--and for analysing overlapping CDSs following frameshift sites. The software, web-server, database and supplementary material are available at http://guinevere.otago.ac.nz/mlogd.html.

Algorithms↗
PubMed2005

Evaluating concentration estimation errors in ELISA microarray experiments.

BACKGROUND: Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to estimate a protein's concentration in a sample. Deploying ELISA in a microarray format permits simultaneous estimation of the concentrations of numerous proteins in a small sample. These estimates, however, are uncertain due to processing error and biological variability. Evaluating estimation error is critical to interpreting biological significance and improving the ELISA microarray process. Estimation error evaluation must be automated to realize a reliable high-throughput ELISA microarray system. In this paper, we present a statistical method based on propagation of error to evaluate concentration estimation errors in the ELISA microarray process. Although propagation of error is central to this method and the focus of this paper, it is most effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization, and statistical diagnostics when evaluating ELISA microarray concentration estimation errors. RESULTS: We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of concentration estimation errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error. We summarize the results with a simple, three-panel diagnostic visualization featuring a scatterplot of the standard data with logistic standard curve and 95% confidence intervals, an annotated histogram of sample measurements, and a plot of the 95% concentration coefficient of variation, or relative error, as a function of concentration. CONCLUSIONS: This statistical method should be of value in the rapid evaluation and quality control of high-throughput ELISA microarray analyses. Applying propagation of error to a variety of ELISA microarray concentration estimation models is straightforward. Displaying the results in the three-panel layout succinctly summarizes both the standard and sample data while providing an informative critique of applicability of the fitted model, the uncertainty in concentration estimates, and the quality of both the experiment and the ELISA microarray process.

Algorithms↗
PubMed2003

CDS annotation in full-length cDNA sequence.

The identification of coding sequences (CDS) is an important step in the functional annotation of genes. CDS prediction for mammalian genes from genomic sequence is complicated by the vast abundance of intergenic sequence in the genome, and provides little information about how different parts of potential CDS regions are expressed. In contrast, mammalian gene CDS prediction from cDNA sequence offers obvious advantages, yet encounters a different set of complexities when performed on high-throughput cDNA (HTC) sequences, such as the set of 60,770 cDNAs isolated from full-length enriched libraries of the FANTOM2 project. We developed a CDS annotation strategy that uses a variety of different CDS prediction programs to annotate the CDS regions of FANTOM2 cDNAs. These include rsCDS, which uses sequence similarity to known proteins; ProCrest; Longest-ORF and Truncated-ORF, which are ab initio based predictors; and finally, DECODER and NCBI CDS predictor, which use a combination of both principles. Aided by graphical displays of these CDS prediction results in the context of other sequence similarity results for each cDNA, FANTOM2 CDS inspection by curators and follow-up quality control procedures resulted in high quality CDS predictions for a total of 14,345 FANTOM2 clones.

Animals↗
PubMed2001

Genomic interspecies microarray hybridization: rapid discovery of three thousand genes in the maize endophyte, Klebsiella pneumoniae 342, by microarray hybridization with Escherichia coli K-12 open reading frames.

In an effort to efficiently discover genes in the diazotrophic endophyte of maize, Klebsiella pneumoniae 342, DNA from strain 342 was hybridized to a microarray containing 96% (n = 4,098) of the annotated open reading frames from Escherichia coli K-12. Using a criterion of 55% identity or greater, 3,000 (70%) of the E. coli K-12 open reading frames were also found to be present in strain 342. Approximately 24% (n = 1,030) of the E. coli K-12 open reading frames are absent in strain 342. For 1.6% (n = 68) of the open reading frames, the signal was too low to make a determination regarding the presence or absence of the gene. Genes with high identity between the two organisms are those involved in energy metabolism, amino acid metabolism, fatty acid metabolism, cofactor synthesis, cell division, DNA replication, transcription, translation, transport, and regulatory proteins. Functions that were less highly conserved included carbon compound metabolism, membrane proteins, structural proteins, putative transport proteins, cell processes such as adaptation and protection, and central intermediary metabolism. Open reading frames of E. coli K-12 with little or no identity in strain 342 included putative regulatory proteins, putative chaperones, surface structure proteins, mobility proteins, putative enzymes, hypothetical proteins, and proteins of unknown function, as well as genes presumed to have been acquired by lateral transfer from sources such as phage, plasmids, or transposons. The results were in agreement with the physiological properties of the two strains. Whole genome comparisons by genomic interspecies microarray hybridization are shown to rapidly identify thousands of genes in a previously uncharacterized bacterial genome provided that the genome of a close relative has been fully sequenced. This approach will become increasingly more useful as more full genome sequences become available.

Escherichia coli↗
PubMed2004

Prediction of sequence signals for lipid post-translational modifications: insights from case studies.

In silico annotation techniques for post-translational modifications (PTMs) are important to generate biologically meaningful descriptions for sequences of experimentally uncharacterized proteins. Having previously contributed with predictors for lipid PTMs, we summarize our methodological experience. Rather than only looking for the sequence pattern in substrate sequences, a strategy aimed at creating a generalized model of substrate protein/enzyme interaction appears more appropriate since the number of known substrate sequences is small, and some of them are not sufficiently verified experimentally. Such a physical approach (in contrast to a mere textual analysis of substrate sequences) can also take into account other, heterogeneous biological data (mutations of substrate sequences, kinetic data, enzyme sequences/structures) with simple analytical expressions in the score function. Several lipid PTMs are encoded in the form of a small sequence region (with pronounced amino acid type preferences) that is connected to the substrate protein by a linker region with many conformationally flexible, hydrophilic residues. A score function composed of terms penalizing sequence properties known to be incompatible with productive substrate protein/enzyme complexes essentially unselects inappropriate queries. Also, we estimate the number of nonredundant sequences necessary for robust profile computation with statistical criteria, a number that is not reached in most cases of PTM prediction. Finally, we discuss the usage of evolutionary information in evaluating the functional importance of predicted PTMs in cases of motif conservation within sequence families.

Acetyltransferases↗
PubMed2026

ChromBERT-tools: a versatile toolkit for context-specific regulatory representations of transcription regulators across different cell types.

SUMMARY: Representations that encode the genome-wide regulatory behavior of transcription regulators provide a foundation for flexible transcription modeling and in silico regulatory analysis. Existing regulator representations are commonly derived from gene co-expression, motif annotations, or static protein features, which capture useful but limited aspects of regulator identity but do not directly model how regulators participate in region-specific regulatory programs across the genome. ChromBERT addresses this gap by learning context-aware regulatory representations from large-scale ChIP-seq data. However, routine bioinformatics applications require lightweight, accessible, and modular tools for generating, adapting, and interpreting these representations in user-defined biological contexts. Here, we present ChromBERT-tools, a user-oriented toolkit built upon ChromBERT that converts its regulatory representation framework into practical workflows for customizable analysis across cellular contexts. ChromBERT-tools provides command-line interfaces and Python APIs organized into three functional layers: representation generation, predictive modeling, and regulatory interpretation. The representation generation layer produces representations of genomic regions and transcription regulators. The predictive modeling layer fine-tunes ChromBERT for genome-wide regulatory activity prediction through classification or regression tasks, with optimized implementation to reduce running time and computational resource requirements. The regulatory interpretation layer supports inference of the context-specific roles of cis-regulatory elements and transcription regulators. These modules can be used independently or integrated into end-to-end workflows, enabling flexible analyses across diverse datasets. ChromBERT-tools lowers the barrier to applying context-specific regulatory representations in routine genomic analyses. AVAILABILITY AND IMPLEMENTATION: ChromBERT-tools is freely available at https://github.com/TongjiZhanglab/ChromBERT-tools, with documentation at https://chrombert-tools.readthedocs.io/en/latest/. A frozen archival snapshot is available on Zenodo under DOI: 10.5281/zenodo.20094206.

Software↗
PubMed2026

pLAST-a tool for rapid comparison and classification of bacterial plasmid sequences.

MOTIVATION: The increasing number of fully sequenced bacterial plasmids being annotated and catalogued has prompted the development of computational tools for comparing and classifying them. Existing approaches typically compare full-length DNA sequences (e.g. Mash, BLASTn, and ANI-based methods) or translated open reading frames (ORFs) (e.g. DIAMOND), with plasmid-level scores obtained by aggregating ORF-to-ORF similarities; however, they are either restricted to closely related plasmids or become computationally demanding in large-scale analyses. RESULTS: We describe pLAST (plasmid Language Analysis and Search Tool), a plasmid-search tool built using word2vec representations of protein-family content informed by local genomic context. Benchmarks indicate that pLAST outperforms nucleotide-based methods and performs comparably to DIAMOND in identifying functionally similar plasmids and compared with the widely used Mash, it achieves 26% and 24% improvements in detecting shared mating-pair formation system type and relaxase type, respectively. This performance scales to database searches across hundreds of thousands of sequences, as demonstrated using the precomputed PlasmidScope collection of ∼750 000 plasmids. Beyond global similarity, pLAST also returns per-ORF plasmid-plasmid alignments, enabling detection of shared functional modules. AVAILABILITY AND IMPLEMENTATION: pLAST is freely accessible as a web server at https://plast.lbs.cent.uw.edu.pl/ or https://plast.lbs.biol.uw.edu.pl/ and available as a Python module along with a precomputed database at https://github.com/labstructbioinf/pLAST for customized analysis.

Plasmids↗