HNHDb: A database on pattern based classification of HNH domains reveals functional relevance of sequence patterns and domain associations.

The HNH Database is a collection and sequence-based classification of HNH domain proteins. The database contains about 1913 HNH domain containing proteins, and is classified into 10 subsets based on the sequence pattern. Each of these subsets has unique signature sequences. We have shown a correlation between the subset combination and their domain association and function. Functional divergence of this domain may be due to the combination of these conserved patterns and the large variations in the non-conserved regions. HNHDb is freely available at http://bicmku.in:8081/hnh.     

sRNAbase: A Web Resource for Small RNAs in Enterobacteriaceae\m{1}

Bacterial small RNAs (sRNAs) have gained considerable attention due to their multivalent roles in the survival and pathogenesis of bacteria and mostly identified through bio-computational methods. A manually curated web-resource, sRNAbase has been constructed to give comprehensive and exhaustive information on non-coding small RNAs excluding tRNAs and rRNAs in Enterobacteriaceae family. The sRNA entries curated in sRNAbase contain experimentally verified small RNAs available in the literature and their partial/non-homologs reported within the related genomes from our earlier studies. The sRNAbase aims to facilitate the scientific community by providing information on the physical genomic location of the non-coding small RNAs, its alias names, sequences, strand orientation, gene identification numbers of the conserved genes that sandwiches the particular sRNA with possible functional role and a link to the PubMed literatures. Currently, sRNAbase holding information on 1986 entries belongs to 80 sRNA families spread over 45 Enterobacteriaceae genomes. The sRNAbase is accessible on the web at http://bicmku.in:8081/srnabase/.     

Disease associated cytokine SNPs database: an annotation and dissemination model

Cytokines mediate crucial functions in innate and adaptive immunity. They play valuable roles in immune cell growth and lineage specification, and are associated with various disease pathologies. A large number of low, medium and high throughput studies have implicated association of single nucleotide polymorphisms (SNPs) in cytokine genes with diseases. A preponderance of such experiments has not shown any causality of an identified SNP to the associated disease. Instead, they have identified statistically significant SNP-disease associations; it is likely that some of these cytokine gene variants may directly or indirectly cause the disease phenotype(s). To fill this knowledge gap and derive study parameters for cytokine SNP-disease causality relationships, we have designed and developed the disease associated cytokine SNP database (DACS-DB). DACS-DB has data on 456 cytokine genes, approximately 63,000 SNPs, and 853 SNP-associated diseases. In DACS-DB, among other attributes, we present functional annotation, and heterozygosity allele frequency for the SNPs, and literature-validated SNP association for diseases. Users of the DB can run queries such as the ones to find disease-associated SNPs in a cytokine gene, and all the SNPs involved in a disease. We have developed a web front end (available at http://www.iupui.edu/~cytosnp) to disseminate this information for immunologists, biomedical researchers, and other interested biological researchers. Since there is no such comprehensive collection of disease associated cytokine SNPs, this DB will be vital to understand the role of cytokine SNPs as markers in disease, and more importantly, in causality to disease thus helping to identify drug targets for common inflammatory diseases.     

ProADD: A database on Protein Aggregation Diseases

ProADD, a database for protein aggregation diseases, is developed to organize the data under a single platform to facilitate easy access for researchers. Diseases caused due to protein aggregation and the proteins involved in each of these diseases are integrated. The database helps in classification of proteins involved in the protein aggregation diseases based on sequence and structural analysis. Analysis of proteins can be done to mine patterns prevailing among the aggregating proteins.

Availability

http://bicmku.in/ProADD     

SNP2NMD: a database of human single nucleotide polymorphisms causing nonsense-mediated mRNA decay

Elucidating the effects of genetic polymorphisms on genes and gene networks is an important step in disease association studies. We developed the SNP2NMD database for human SNPs (single nucleotide polymorphisms) that result in PTCs (premature termination codons) and trigger nonsense-mediated mRNA decay (NMD). The SNP2NMD Web interfaces provide extensive genetic information on and graphical views of the queried SNP, gene, and disease terms. Availability: SNP2NMD is available from http://variome.net, or directly from http://bioportal.kobic.re.kr/SNP2NMD. Supplementary information: http://bioportal.kobic.re.kr/SNP2NMD/Wiki.jsp?page=Statistics.     

Single nucleotide polymorphism discovery in barley using autoSNPdb

Molecular markers are used to provide the link between genotype and phenotype, for the production of molecular genetic maps and to assess genetic diversity within and between related species. Single nucleotide polymorphisms (SNPs) are the most abundant molecular genetic marker. SNPs can be identified in silico , but care must be taken to ensure that the identified SNPs reflect true genetic variation and are not a result of errors associated with DNA sequencing. The SNP detection method autoSNP has been developed to identify SNPs from sequence data for any species. Confidence in the predicted SNPs is based on sequence redundancy, and haplotype co-segregation scores are calculated for a further independent measure of confidence. We have extended the autoSNP method to produce autoSNPdb, which integrates SNP and gene annotation information with a graphical viewer. We have applied this software to public barley expressed sequences, and the resulting database is available over the Internet. SNPs can be viewed and searched by sequence, functional annotation or predicted synteny with a reference genome, in this case rice. The correlation between SNPs and barley cultivar, expressed tissue type and development stage has been collated for ease of exploration. An average of one SNP per 240 bp was identified, with SNPs more prevalent in the 5' regions and simple sequence repeat (SSR) flanking sequences. Overall, autoSNPdb can provide a wealth of genetic polymorphism information for any species for which sequence data are available.     

SNPdbe: constructing an nsSNP functional impacts database

Many existing databases annotate experimentally characterized single nucleotide polymorphisms (SNPs). Each non-synonymous SNP (nsSNP) changes one amino acid in the gene product (single amino acid substitution;SAAS). This change can either affect protein function or be neutral in that respect. Most polymorphisms lack experimental annotation of their functional impact. Here, we introduce SNPdbe-SNP database of effects, with predictions of computationally annotated functional impacts of SNPs. Database entries represent nsSNPs in dbSNP and 1000 Genomes collection, as well as variants from UniProt and PMD. SAASs come from >2600 organisms; 'human' being the most prevalent. The impact of each SAAS on protein function is predicted using the SNAP and SIFT algorithms and augmented with experimentally derived function/structure information and disease associations from PMD, OMIM and UniProt. SNPdbe is consistently updated and easily augmented with new sources of information. The database is available as an MySQL dump and via a web front end that allows searches with any combination of organism names, sequences and mutation IDs. AVAILABILITY: http://www.rostlab.org/services/snpdbe.     

A mutation spectra database for bacterial and mammalian genes.

Each mutation spectrum in this database is a dataset of changes in DNA base sequence in mutations induced in a gene by a particular mutagen (including spontaneous processes) under defined conditions. There are 240 datasets with 24 500 mutants in nine bacterial genes, two phage genes, five mammalian genes and one yeast gene. The database is available on the Web at http://info.med.yale.edu/mutbase/ . The data tables can be viewed on the Web and downloaded in text form for local use. The data are also available in dBASE III, a format which can be utilized by essentially any desktop computer database program or spreadsheet, and makes feasible analyses of a large number of mutants. Researchers are invited to submit additional data. A data entry program, MUTSIN, diagrams each mutation on the computer screen as the data are entered and alerts the user to any discrepancies between the entry and the gene sequence.     

RiDs db: Repeats in diseases database

The non-coding fraction of the human genome, which is approximately 98%, is mainly constituted by repeats. Transpositions, expansions and deletions of these repeat elements contribute to a number of diseases. None of the available databases consolidates information on both tandem and interspersed repeats with the flexibility of FASTA based homology search with reference to disease genes. Repeats in diseases database (RiDs db) is a web accessible relational database, which aids analysis of repeats associated with Mendelian disorders. It is a repository of disease genes, which can be searched by FASTA program or by limitedor free- text keywords. Unlike other databases, RiDs db contains the sequences of these genes with access to corresponding information on both interspersed and tandem repeats contained within them, on a unified platform. Comparative analysis of novel or patient sequences with the reference sequences in RiDs db using FASTA search will indicate change in structure of repeats, if any, with a particular disorder. This database also provides links to orthologs in model organisms such as zebrafish, mouse and Drosophila. AVAILABILITY: The database is available for free at http://115.111.90.196/ridsdb/index.php.     

PRIME: automatically extracted PRotein Interactions and Molecular Information databasE

With the exponentially increasing amount of information in the biomedical field, the significance of advanced information retrieval and information extraction, as well as the role of databases, has been increasing. PRIME is an integrated gene/protein informatics database based on natural language processing. It provides automatically extracted protein/family/gene/compound interaction information including both physical and genetic interactions, gene ontology based functions, and graphic pathway viewers. Gene/protein/family names and functional terms are recognized based on dictionaries developed in our laboratory. The interaction and functional information are extracted by syntactic dependencies and various phrase patterns. We have included about 920,000 (non-redundant) protein interactions and 360,000 annotated gene-function relationships for major eukaryotes. By combining the sequence and text information, the pathway comparison between two organisms and simple pathway deduction based on other organism interaction data, and pathway filtering using tissue expression data, are also available. This database is accessible at http://prime.ontology.ims.u-tokyo.ac.jp:8081.     

A Laboratory Information Management System (LIMS) for a high throughput genetic platform aimed at candidate gene mutation screening

High throughput mutation screening in an automated environment generates large data sets that have to be organized and stored reliably. Complex multistep workflows require strict process management and careful data tracking. We have developed a Laboratory Information Management Systems (LIMS) tailored to high throughput candidate gene mutation scanning and resequencing that respects these requirements. Designed with a client/server architecture, our system is platform independent and based on open-source tools from the database to the web application development strategy. Flexible, expandable and secure, the LIMS, by communicating with most of the laboratory instruments and robots, tracks samples and laboratory information, capturing data at every step of our automated mutation screening workflow. An important feature of our LIMS is that it enables tracking of information through a laboratory workflow where the process at one step is contingent on results from a previous step. AVAILABILITY: Script for MySQL database table creation and source code of the whole JSP application are freely available on our website: http://www-gcs.iarc.fr/lims/. SUPPLEMENTARY INFORMATION: System server configuration, database structure and additional details on the LIMS and the mutation screening workflow are available on our website: http://www-gcs.iarc.fr/lims/     

LSHGD: A database for human leprosy susceptible genes

Studies aiming to explore the involvement of host genetic factors to determine susceptibility to develop disease and individual's response to the infection with Mycobacterium leprae have increased in recent years. To address this issue, we have developed a Leprosy Susceptible Human Gene Database (LSHGD) to integrate leprosy and human associated 45 genes by profound literature search. This will serve as a user-friendly and interactive platform to understand the involvement of human polymorphisms (SNPs) in leprosy, independent genetic control over both susceptibility to leprosy and its association with multi-drug resistance of M. leprae. As the first human genetic database in leprosy it aims to provide information about the associated genes, corresponding protein sequences, available three dimensional structures and polymorphism related to leprosy. In conclusion, this will serve as a multifunctional valuable tool and convenient information platform which is freely available at http://www.vit.ac.in/leprosy/leprosy.htm and enables the user to retrieve information of their interest.     

HGVbase: a human sequence variation database emphasizing data quality and a broad spectrum of data sources

HGVbase (Human Genome Variation database; http://hgvbase.cgb.ki.se, formerly known as HGBASE) is an academic effort to provide a high quality and non-redundant database of available genomic variation data of all types, mostly comprising single nucleotide polymorphisms (SNPs). Records include neutral polymorphisms as well as disease-related mutations. Online search tools facilitate data interrogation by sequence similarity and keyword queries, and searching by genome coordinates is now being implemented. Downloads are freely available in XML, Fasta, SRS, SQL and tagged-text file formats. Each entry is presented in the context of its surrounding sequence and many records are related to neighboring human genes and affected features therein. Population allele frequencies are included wherever available. Thorough semi-automated data checking ensures internal consistency and addresses common errors in the source information. To keep pace with recent growth in the field, we have developed tools for fully automated annotation. All variants have been uniquely mapped to the draft genome sequence and are referenced to positions in EMBL/GenBank files. Data utility is enhanced by provision of genotyping assays and functional predictions. Recent data structure extensions allow the capture of haplotype and genotype information, and a new initiative (along with BiSC and HUGO-MDI) aims to create a central repository for the broad collection of clinical mutations and associated disease phenotypes of interest.     

BCDB - A database for breast cancer research and information

In pursuit of a better updated source including 'omics' information for breast cancer, Breast Cancer Database (BCDB) has been developed to provide the researcher with the quick overview of the Breast cancer disease and other relevant information. This database comprises of myriad of information about genes involved in breast cancer, its functions and drug molecules which are currently being used in the treatment of breast cancer. The data available in BCDB is retrieved from the biomedical research literature. It facilitates the user to search information on gene, its location in chromosome, functions and its importance in cancer diseases. Broadly, this can be queried by giving gene name, protein name and drug name. This database is platform independent, user friendly and freely accessible through internet. The data present in BCDB is directly linked to other on-line resources such as NCBI, PDB and PubMed. Hence, it can act as a complete web resource comprising gene sequences, drug structures and literature information related to breast cancer, which is not available in any other breast cancer database. AVAILABILITY: The database is freely available at http://122.165.25.137/bioinfo/breastcancerdb/     

Data integration workflow for search of disease driving genes and genetic variants

Comprehensive characterization of a gene's impact on phenotypes requires knowledge of the context of the gene. To address this issue we introduce a systematic data integration method Candidate Genes and SNPs (CANGES) that links SNP and linkage disequilibrium data to pathway- and protein-protein interaction information. It can be used as a knowledge discovery tool for the search of disease associated causative variants from genome-wide studies as well as to generate new hypotheses on synergistically functioning genes. We demonstrate the utility of CANGES by integrating pathway and protein-protein interaction data to identify putative functional variants for (i) the p53 gene and (ii) three glioblastoma multiforme (GBM) associated risk genes. For the GBM case, we further integrate the CANGES results with clinical and genome-wide data for 209 GBM patients and identify genes having effects on GBM patient survival. Our results show that selecting a focused set of genes can result in information beyond the traditional genome-wide association approaches. Taken together, holistic approach to identify possible interacting genes and SNPs with CANGES provides a means to rapidly identify networks for any set of genes and generate novel hypotheses. CANGES is available in http://csbi.ltdk.helsinki.fi/CANGES/