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Biomedical subjects

P Bala

Publications and source records attributed to P Bala.

8 recordsLinked to original sources

Human protein reference database--2006 update.

Human Protein Reference Database (HPRD) (http://www.hprd.org) was developed to serve as a comprehensive collection of protein features, post-translational modifications (PTMs) and protein-protein interactions. Since the original report, this database has increased to >20 000 proteins entries and has become the largest database for literature-derived protein-protein interactions (>30 000) and PTMs (>8000) for human proteins. We have also introduced several new features in HPRD including: (i) protein isoforms, (ii) enhanced search options, (iii) linking of pathway annotations and (iv) integration of a novel browser, GenProt Viewer (http://www.genprot.org), developed by us that allows integration of genomic and proteomic information. With the continued support and active participation by the biomedical community, we expect HPRD to become a unique source of curated information for the human proteome and spur biomedical discoveries based on integration of genomic, transcriptomic and proteomic data.

Databases, Protein↗

TAGmapper: a web-based tool for mapping SAGE tags.

Serial Analysis of Gene Expression (SAGE) is an important means of obtaining quantitative information about expression of genes in different samples. Short SAGE tags are 10 nucleotides long and often contain enough information to uniquely identify the gene(s) corresponding to the tag. We have observed, however, that the currently available resources are not adequate for accurate mapping of all SAGE tags to genes. Here, we describe development of a web-based tool called TAGmapper (http://tagmapper.ibioinformatics.org), which provides a comprehensive and accurate mapping of SAGE tags to genes. We were able to map SAGE tags accurately in several instances where two other popular resources, SAGEmap (http://www.ncbi.nlm.nih.gov/projects/SAGE/) and SAGE Genie (http://cgap.nci.nih.gov/SAGE), provided incorrect or no assignment of tags to genes. Finally, we experimentally determined the expression of a subset of genes assigned by TAGmapper using DNA microarrays and/or quantitative PCR to confirm the reliability of the gene mappings. We anticipate that TAGmapper will be a useful tool in functional genomic approaches by providing accurate identification of genes in SAGE experiments.

Base Sequence↗

Plasma Proteome Database as a resource for proteomics research.

Plasma is one of the best studied compartments in the human body and serves as an ideal body fluid for the diagnosis of diseases. This report provides a detailed functional annotation of all the plasma proteins identified to date. In all, gene products encoded by 3778 distinct genes were annotated based on proteins previously published in the literature as plasma proteins and the identification of multiple peptides from proteins under HUPO's Plasma Proteome Project. Our analysis revealed that 51% of these genes encoded more than one protein isoform. All single nucleotide polymorphisms involving protein-coding regions were mapped onto the protein sequences. We found a number of examples of isoform-specific subcellular localization as well as tissue expression. This database is an attempt at comprehensive annotation of a complex subproteome and is available on the web at http://www.plasmaproteomedatabase.org.

Amino Acid Motifs↗

A study of effects of acid activated saw dust on the removal of different dissolved tannery dyes (acid dye) from aqueous solutions.

The effectiveness of acid activated sawdust in absorbing D-Brown EGP and Lurazol Brown PM dyes from aqueous solutions was studied as a function of agitation time and initial dye concentration. The experimental data were fitted to Langmuir and Freundlich isotherm and found that adsorption process follows both the isotherms. The values of Langmuir and Freundlich constants indicate favorable and beneficial adsorption. Saw dust is an excellent low cost adsorbent of colored organic anions and may have significant potential as a color removal from tannery wastewater.

Acids↗

Identification of novel highly expressed genes in pancreatic ductal adenocarcinomas through a bioinformatics analysis of expressed sequence tags.

In most microarray experiments, a significant fraction of the differentially expressed mRNAs identified correspond to expressed sequence tags (ESTs) and are generally discarded from further analyses. We used careful bioinformatics analyses to characterize those ESTs that were found to be highly overexpressed in a series of pancreatic adenocarcinomas. cDNA was prepared from 60 non-neoplastic samples (normal pancreas [n = 20], normal colon [n = 10], or normal duodenal mucosal [n = 30]) and from 64 pancreatic cancers (resected cancers [n = 50] or cancer cell lines [n = 14]) and hybridized to the complete Affymetrix Human Genome U133 GeneChip(R) set (arrays U133A and B) for simultaneous analysis of 45,000 fragments corresponding to 33,000 known genes and 6,000 ESTs. The GeneExpress(R) software system Fold Change Analysis Tool was used and 60 ESTs were identified that were expressed at levels at least 3-fold greater in the pancreatic cancers as compared to normal tissues. Searches against the human genomic sequence and comparative genomic analysis of human and mouse genomes was carried out using basic local alignment search tools (BLAST), BLASTN, and BLASTX, for identifying protein coding genes corresponding to the ESTs. Subsequently, in order to pick the most relevant candidate genes for a more detailed analysis, we looked for domains/motifs in the open reading frames using SMART and Pfam programs. We were able to definitively map 43 of the 60 ESTs to known or novel genes, and 15 of the ESTs could be localized in close proximity to a gene in the human genome although we were unable to establish that the EST was indeed derived from those genes. The differential expression of a subset of genes was confirmed at the protein level by immunohistochemical labeling of tissue microarrays (inhibin beta A [INHBA] and CD29) and/or at the transcript level by RT-PCR (INHBA, AKAP12, ELK3, FOXQ1, EIF5A2, and EFNA5). We conclude that bioinformatics tools can be used to characterize differentially overexpressed ESTs, and that some of these ESTs may represent diagnostically and therapeutically useful targets that might be missed using data solely from currently annotated databases.

Adenocarcinoma↗