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At least 1,117 records · Page 62Linked to original sources
PubMed2006

Curation of complex, context-dependent immunological data.

BACKGROUND: The Immune Epitope Database and Analysis Resource (IEDB) is dedicated to capturing, housing and analyzing complex immune epitope related data http://www.immuneepitope.org. DESCRIPTION: To identify and extract relevant data from the scientific literature in an efficient and accurate manner, novel processes were developed for manual and semi-automated annotation. CONCLUSION: Formalized curation strategies enable the processing of a large volume of context-dependent data, which are now available to the scientific community in an accessible and transparent format. The experiences described herein are applicable to other databases housing complex biological data and requiring a high level of curation expertise.

Allergy and Immunology↗
PubMed2005

MAASE: an alternative splicing database designed for supporting splicing microarray applications.

Alternative splicing is a prominent feature of higher eukaryotes. Understanding of the function of mRNA isoforms and the regulation of alternative splicing is a major challenge in the post-genomic era. The development of mRNA isoform sensitive microarrays, which requires precise splice-junction sequence information, is a promising approach. Despite the availability of a large number of mRNAs and ESTs in various databases and the efforts made to align transcript sequences to genomic sequences, existing alternative splicing databases do not offer adequate information in an appropriate format to aid in splicing array design. Here we describe our effort in constructing the Manually Annotated Alternatively Spliced Events (MAASE) database system, which is specifically designed to support splicing microarray applications. MAASE comprises two components: (1) a manual/computational annotation tool for the efficient extraction of critical sequence and functional information for alternative splicing events and (2) a user-friendly database of annotated events that allows convenient export of information to aid in microarray design and data analysis. We provide a detailed introduction and a step-by-step user guide to the MAASE database system to facilitate future large-scale annotation efforts, integration with other alternative splicing databases, and splicing array fabrication.

Alternative Splicing↗
PubMed2005

Computationally analyzing the possible biological function of YJL103C--an ORF potentially involved in the regulation of energy process in yeast.

Although the complete genomes of a number of organisms have been sequenced, the biological functions of many genes are still not known. Because experimentally studying the functions of those genes one by one requires tremendous time, it is vital to use published resources like microarray gene expression data for computational analysis of gene functions. One example is YJL103C, a yeast gene of unknown function in the Saccharomyces Genome Database (SGD). It is possible to quickly infer its biological function by computational analysis. In this study, we present an efficient model to explore the biological function of a novel gene using microarray data. We showed that the expression pattern of YJL103C is most similar to the genes in the energy group and respiratory chain subgroup. We further found that YJL103C contains a HAP2,3,4 box in its promoter region and a cytochrome C heme-binding signature in its protein sequence. Our findings define a potential role for YJL103C in the regulation of energy metabolism, specifically in the process of oxidative phosphorylation. Similar bioinformatics methods can be applied to infer the biological functions of other novel genes in organisms for which microarray data are available. In this work, we selected a single gene of unknown function as a case study. By focusing on the power of computer analysis and bioinformatics on the available microarray data, we have determined the likely biological function of YJL103C. Our study provides a method by which to explore the potential function of other genes currently annotated as having an unknown function in any organism for which global gene expression data are available.

Binding Sites↗
PubMed2002

DNA Methylation Database "MethDB": a user guide.

The DNA Methylation Database (MethDB; http://www.methdb.net) is a public database dedicated to DNA methylation. It attempts to store all data about DNA methylation in a common source. MethDB can be searched in different ways, ranging from a simple browse mode to detailed queries for sequence-specific DNA methylation profiles and patterns, total methylation content data or environmental conditions that can influence the methylation state of DNA. Currently, the database contains 2570 values for methylation content and 5278 methylation patterns and profiles for a total of 83 genes or loci. MethDB is an annotated database, and the scientific community is invited to submit their own data (submit@methdb.de).

Computer Graphics↗
PubMed2026

DeepMASS v.2: An enhanced deep learning platform for large-scale discovery and structural annotation of unknown plant metabolites.

Determining the structures of unknown metabolites remains a fundamental bottleneck in plant metabolomics, as the vast chemical diversity of plant secondary metabolites far exceeds the coverage of existing spectral libraries. Here, we present DeepMASS v.2, a substantially enhanced platform for annotating unknown metabolites from liquid chromatography-tandem mass spectrometry data, designed to address this challenge at scale. DeepMASS v.2 leverages a semantic spectral representation model trained on millions of spectra from GNPS, NIST, and in-house resources. By integrating Spec2Vec-based embeddings with HNSW (hierarchical navigable small world) graph retrieval and a unified chemical space defined by molecular fingerprints, DeepMASS v.2 identifies structurally related neighbors of unknown spectra and ranks candidate structures according to their proximity to the predicted structural neighborhoods within chemical space. Benchmarking against Critical Assessment of Small Molecule Identification datasets and a curated natural product collection demonstrated that DeepMASS v.2 outperforms state-of-the-art in silico annotation tools, including SIRIUS, CFM-ID, MetFrag, and MS-Finder. Importantly, DeepMASS v.2 maintains strong performance for metabolites absent from spectral libraries, highlighting its capacity to annotate genuinely unknown compounds. Application of DeepMASS v.2 to large-scale plant metabolomics datasets demonstrated its ability to expand accessible metabolome coverage. Implemented as an intuitive web platform, DeepMASS v.2 provides the community with a scalable, interpretable, and high-throughput solution for structural annotation, enabling more comprehensive characterization of plant chemical diversity and accelerating natural product discovery in molecular plant science. The DeepMASS v.2 web server is publicly available at http://deepmass.cn.

Metabolomics↗
PubMed2004

The mouse genome: experimental examination of gene predictions and transcriptional start sites.

The completion of the mouse and other mammalian genome sequences will provide necessary, but not sufficient, knowledge for an understanding of much of mouse biology at the molecular level. As a requisite next step in this process, the genes in mouse and their structure must be elucidated. In particular, knowledge of the transcriptional start site of these genes will be necessary for further study of their regulatory regions. To assess the current state of mouse genome annotation to support this activity, we identified several hundred gene predictions in mouse with varying levels of supporting evidence and tested them using RACE-PCR. Modifications were made to the procedure allowing pooling of RNA samples, resulting in a scaleable procedure. The results illustrate potential errors or omissions in the current 5' end annotations in 58% of the genes detected. In testing experimentally unsupported gene predictions, we were able to identify 58 that are not usually annotated as genes but produced spliced transcripts (approximately 25% success rate). In addition, in many genes we were able to detect novel exons not predicted by any gene prediction algorithms. In 19.8% of the genes detected in this study, multiple transcript species were observed. These data show an urgent need to provide direct experimental validation of gene annotations. Moreover, these results show that direct validation using RACE-PCR can be an important component of genome-wide validation. This approach can be a useful tool in the ongoing efforts to increase the quality of gene annotations, especially transcriptional start sites, in complex genomes.

Animals↗
PubMed2003

GAMOLA: a new local solution for sequence annotation and analyzing draft and finished prokaryotic genomes.

Laboratories working with draft phase genomes have specific software needs, such as the unattended processing of hundreds of single scaffolds and subsequent sequence annotation. In addition, it is critical to follow the "movement" and the manual annotation of single open reading frames (ORFs) within the successive sequence updates. Even with finished genomes, regular database updates can lead to significant changes in the annotation of single ORFs. In functional genomics it is important to mine data and identify new genetic targets rapidly and easily. Often there is no need for sophisticated relational databases (RDB) that greatly reduce the system-independent access of the results. Another aspect is the internet dependency of most software packages. If users are working with confidential data, this dependency poses a security issue. GAMOLA was designed to handle the numerous scaffolds and changing contents of draft phase genomes in an automated process and stores the results for each predicted ORF in flatfile databases. In addition, annotation transfers, ORF designation tracking, Blast comparisons, and primer design for whole genome microarrays have been implemented. The software is available under the license of North Carolina State University. A website and a downloadable example are accessible under (http://fsweb2.schaub. ncsu.edu/TRKwebsite/index.htm).

Algorithms↗
PubMed2006

LS-NMF: a modified non-negative matrix factorization algorithm utilizing uncertainty estimates.

BACKGROUND: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to identify patterns that together explain the data as a linear combination of expression signatures. Microarray data generally includes individual estimates of uncertainty for each gene in each condition, however NMF does not exploit this information. Previous work has shown that such uncertainties can be extremely valuable for pattern recognition. RESULTS: We have created a new algorithm, least squares non-negative matrix factorization, LS-NMF, which integrates uncertainty measurements of gene expression data into NMF updating rules. While the LS-NMF algorithm maintains the advantages of original NMF algorithm, such as easy implementation and a guaranteed locally optimal solution, the performance in terms of linking functionally related genes has been improved. LS-NMF exceeds NMF significantly in terms of identifying functionally related genes as determined from annotations in the MIPS database. CONCLUSION: Uncertainty measurements on gene expression data provide valuable information for data analysis, and use of this information in the LS-NMF algorithm significantly improves the power of the NMF technique.

Algorithms↗
PubMed2001

Sequence evaluation of four pooled-tissue normalized bovine cDNA libraries and construction of a gene index for cattle.

An essential component of functional genomics studies is the sequence of DNA expressed in tissues of interest. To provide a resource of bovine-specific expressed sequence data and facilitate this powerful approach in cattle research, four normalized cDNA libraries were produced and arrayed for high-throughput sequencing. The libraries were made with RNA pooled from multiple tissues to increase efficiency of normalization and maximize the number of independent genes for which sequence data were obtained. Target tissues included those with highest likelihood to have impact on production parameters of animal health, growth, reproductive efficiency, and carcass merit. Success of normalization and inter- and intralibrary redundancy were assessed by collecting 6000-23,000 sequences from each of the libraries (68,520 total sequences deposited in GenBank). Sequence comparison and assembly of these sequences was performed in combination with 56,500 other bovine EST sequences present in the GenBank dbEST database to construct a cattle Gene Index (available from The Institute for Genomic Research at http://www.tigr.org/tdb/tgi.shtml). The 124,381 bovine ESTs present in GenBank at the time of the analysis form 16,740 assemblies that are listed and annotated on the Web site. Analysis of individual library sequence data indicates that the pooled-tissue approach was highly effective in preparing libraries for efficient deep sequencing.

Animals↗
PubMed2006

Using ontologies to annotate microarray experiments.

Consistent annotation of studies using microarrays is critical to optimal management and use of microarray data. Ontologies provide defined and structured terminology suited for this purpose. The Gene Ontology (GO) has aided the analysis of expression studies greatly by providing consistent functional annotation of array sequence features. The intent of the MGED Ontology (MO) is to provide consistent experimental annotation. The MO has been developed as a community effort in support of the Minimum Information About a Microarray Experiment standard and is tied to the Microarray Gene Expression object model. The MO is freely available and has been incorporated into the annotation systems of several public microarray database systems.

Animals↗
PubMed2002

TAIR: a resource for integrated Arabidopsis data.

The Arabidopsis Information Resource (TAIR; http://arabidopsis.org) provides an integrated view of genomic data for Arabidopsis thaliana. The information is obtained from a battery of sources, including the Arabidopsis user community, the literature, and the major genome centers. Currently TAIR provides information about genes, markers, polymorphisms, maps, sequences, clones, DNA and seed stocks, gene families and proteins. In addition, users can find Arabidopsis publications and information about Arabidopsis researchers. Our emphasis is now on incorporating functional annotations of genes and gene products, genome-wide expression, and biochemical pathway data. Among the tools developed at TAIR, the most notable is the Sequence Viewer, which displays gene annotation, clones, transcripts, markers and polymorphisms on the Arabidopsis genome, and allows zooming in to the nucleotide level. A tool recently released is AraCyc, which is designed for visualization of biochemical pathways. We are also developing tools to extract information from the literature in a systematic way, and building controlled vocabularies to describe biological concepts in collaboration with other database groups. A significant new feature is the integration of the ABRC database functions and stock ordering system, which allows users to place orders for seed and DNA stocks directly from the TAIR site.

Arabidopsis↗
PubMed2001

A functional update of the Escherichia coli K-12 genome.

BACKGROUND: Since the genome of Escherichia coli K-12 was initially annotated in 1997, additional functional information based on biological characterization and functions of sequence-similar proteins has become available. On the basis of this new information, an updated version of the annotated chromosome has been generated. RESULTS: The E. coli K-12 chromosome is currently represented by 4,401 genes encoding 116 RNAs and 4,285 proteins. The boundaries of the genes identified in the GenBank Accession U00096 were used. Some protein-coding sequences are compound and encode multimodular proteins. The coding sequences (CDSs) are represented by modules (protein elements of at least 100 amino acids with biological activity and independent evolutionary history). There are 4,616 identified modules in the 4,285 proteins. Of these, 48.9% have been characterized, 29.5% have an imputed function, 2.1% have a phenotype and 19.5% have no function assignment. Only 7% of the modules appear unique to E. coli, and this number is expected to be reduced as more genome data becomes available. The imputed functions were assigned on the basis of manual evaluation of functions predicted by BLAST and DARWIN analyses and by the MAGPIE genome annotation system. CONCLUSIONS: Much knowledge has been gained about functions encoded by the E. coli K-12 genome since the 1997 annotation was published. The data presented here should be useful for analysis of E. coli gene products as well as gene products encoded by other genomes.

Bacterial Proteins↗
PubMed2004

Exploring the chemogenomic knowledge space with annotated chemical libraries.

The recent human genome initiatives have led to the discovery of a multitude of genes that are potentially associated with various pathologic conditions and, thus, have opened new horizons in drug discovery. Simultaneously, annotated chemical libraries have emerged as information-rich databases to integrate biological and chemical data. They can be useful for the discovery of new pharmaceutical leads, the validation of new biotargets and the determination of the structural basis of ligand selectivity within target families. Annotated libraries provide a strong information basis for computational design of target-directed combinatorial libraries, which are a key component of modern drug discovery. Today, the rational design of chemical libraries enhanced with chemogenomics data is a new area of progressive research.

Combinatorial Chemistry Techniques↗
PubMed2025

Bayesian reconstruction and differential testing of excised introns.

MOTIVATION: Characterizing the differential excision of introns is critical for understanding the functional complexity of a cell or tissue, from normal developmental processes to disease pathogenesis. Most transcript reconstruction methods infer full-length transcripts from high-throughput sequencing data. However, this is a challenging task due to incomplete annotations and the heterogeneous expression of transcripts across cell-types, tissues, and experimental conditions. Several recent methods circumvent these difficulties by considering local splicing events, but these methods lose transcript-level splicing information and may conflate similar, but distinct transcripts. RESULTS: In this work, we formalize a new transcript reconstruction problem that interpolates between the full-length and local splicing perspectives by considering sequences of exon-exon junctions (SEEJs) that co-occur in transcripts. We then present a hierarchical Bayesian admixture model and posterior inference algorithms for computing SEEJs (BSEEJ), and a generalized linear model for characterizing differential SEEJ usage based on model parameter estimates. We show that BSEEJ achieves high F1 score for reconstruction tasks and improved accuracy and sensitivity in differential splicing when compared with six transcript and local splicing methods on simulated data. Lastly, we evaluate BSEEJ on experimental data based on transcript reconstruction, novelty of transcripts produced, model sensitivity to hyperparameters, and a functional analysis of differentially expressed SEEJs. AVAILABILITY AND IMPLEMENTATION: BSEEJ is freely available at https://github.com/bayesomicslab/BSEEJ.

Bayes Theorem↗
PubMedDate not supplied

Genomic messaging system language including command extensions for clinical data categories.

This paper, in the area of clinical bioinformatics, highlights relatively efficient means of storing, exchanging, protecting, and searching human and other genomic data, so as to make the data securely accessible to researchers while respecting patient privacy. One important idea is that the GMSL language can be considered as an extension of the way DNA and protein sequences are written so as to carry with them the wishes of the patient in regard to fine-grained consent (as well as retaining the medical experts' cautions, instructions for use, and annotation), and this is carried, whatever environment (e.g., XML) that the data is from or whatever it is going to. At the deepest level, a stream of data expressed in GMSL resembles highly compressed stream of self-checking machine code. For the reader less familiar with the computational aspects, some simple examples illustrate how the raw language looks and works as a raw stream of (interpreted) bytes. The bioinformatics applications are not confined to the clinical domain. This paper completes the initial specification of the language as previously presented and reports on some important extensions including clinical data categories.

Base Sequence↗
PubMed2005

Adding some SPICE to DAS.

UNLABELLED: The distributed annotation system (DAS) defines a communication protocol used to exchange biological annotations. It is motivated by the idea that annotations should not be provided by single centralized databases but instead be spread over multiple sites. Data distribution, performed by DAS servers, is separated from visualization, which is carried out by DAS clients. The original DAS protocol was designed to serve annotation of genomic sequences. We have extended the protocol to be applicable to macromolecular structures. Here we present SPICE, a new DAS client that can be used to visualize protein sequence and structure annotations. AVAILABILITY: http://www.efamily.org.uk/software/dasclients/spice/

Algorithms↗
PubMed2002

Controlling methicillin-resistant Staphylococcus aureus: a feedback approach using annotated statistical process control charts.

OBJECTIVES: To investigate the benefit of a hospitalwide feedback program regarding methicillin-resistant Staphylococcus aureus (MRSA), using annotated statistical process control charts. DESIGN: Retrospective and prospective analysis of MRSA rates using statistical process control charts. PARTICIPANTS: Twenty-four medical, medical specialty, surgical, intensive care, and cardiothoracic care wards and units at four Glasgow Royal Infirmary hospitals. METHODS: Annotated control charts were applied to prospective and historical monthly data on MRSA cases from each ward and unit during a 46-month period from January 1997 through September 2000. Results were fed back from December 1999 and then on a regular monthly basis to medical staff, ward managers, senior managers, and hotel services. RESULTS: Monthly reductions in the MRSA acquisition rate started 2 months after the introduction of the feedback program and have continued to the present time. The overall MRSA rate currently is approximately 50% lower than when the program began and has become more consistent and less variable within departments throughout Glasgow Royal Infirmary. The control charts have helped to detect rate changes and manage resources more effectively. Medical and nursing staff and managers also report that they find this the most positive form of MRSA feedback they have received. CONCLUSIONS: Feedback programs that provide current information to front-line staff and incorporate annotated control charts can be effective in reducing the rate of MRSA.

Humans↗
PubMed2006

FeatureMap3D--a tool to map protein features and sequence conservation onto homologous structures in the PDB.

FeatureMap3D is a web-based tool that maps protein features onto 3D structures. The user provides sequences annotated with any feature of interest, such as post-translational modifications, protease cleavage sites or exonic structure and FeatureMap3D will then search the Protein Data Bank (PDB) for structures of homologous proteins. The results are displayed both as an annotated sequence alignment, where the user-provided annotations as well as the sequence conservation between the query and the target sequence are displayed, and also as a publication-quality image of the 3D protein structure with the selected features and sequence conservation enhanced. The results are also returned in a readily parsable text format as well as a PyMol (http://pymol.sourceforge.net/) script file, which allows the user to easily modify the protein structure image to suit a specific purpose. FeatureMap3D can also be used without sequence annotation, to evaluate the quality of the alignment of the input sequences to the most homologous structures in the PDB, through the sequence conservation colored 3D structure visualization tool. FeatureMap3D is available at: http://www.cbs.dtu.dk/services/FeatureMap3D/.

Amino Acid Sequence↗