Aims to create a knockout allele in every protein coding gene in the zebrafish genome, using a combination of whole exome enrichment and Illumina next generation sequencing. Each allele created is analysed for morphological differences and published on the ZMP site. Transcript counting is performed on alleles with a morphological phenotype.
Enables you to explore mutation hotspots identified in protein domains from more than 5000 patients across 22 cancer types. Using multiple sequence analysis, protein domain hotspots are identified by tallying missense mutations across analogous residues of domain-containing genes. By taking a domain-centric approach, we identify new mutation hotspots in domains of genes not previously associated with cancer and predict the functional role of many rare mutations. MutationAligner allows researchers to search, browse and analyze cancer mutations in the context of protein domains.
An archive for collecting, managing and searching information of the T-DNA insertion mutants generated by an enhancer trap system. RMD can be searched by keywords, nucleotide sequence or protein sequence. This database provides three classes of functions: (1) identifying novel genes, (2) identifying regulatory elements, and (3) identifying pattern lines for ectopic expression (misexpression) of target gene at specific tissue or at specific growth stage.
It is designed for providing a comprehensive, integrated and well-annotated resource, focusing on protein sequence-altering variations originated from both germline and cancer-associated somatic variations. The mutated protein sequence pool was based on the exome sequencing results of NCI-60 cell lines, the Cancer Cell Line Encyclopedia (CCLE) and 5,600 more cases from 20 TCGA cancer genomics studies.
A database for conveniently accessing the comprehensive information and relationships of spectra, peptides and proteins of single amino-acid polymorphisms (SAPs), as well as related genes, pathways, diseases and drug targets. dbSAP is a customized protein database that contained comprehensive variant proteins by integrating and annotating the human single nucleotide polymorphisms (SNPs) and mutations from eight distinct databases (UniProt, Protein Mutation Database, HPMD, MSIPI, MS-CanProVar, dbSNP, Ensembl and COSMIC). After a series of quality controls, a total of 16,854 SAP peptides involving in 439,537 spectra were identified with large scale mass spectrometry datasets from various human tissues and cell lines. dbSAP is freely available online.
Stores and characterizes cancer-related alterations of single amino acid in the human proteome as well as variations detected in normal samples. CanProVar 2.0 allows users to retrieve protein-level annotations about a variation, such as the corresponding cancer samples, publications, and potential functional impact as suggested by analyses based on evolution conservation, protein expression, protein domains, and protein 3D interaction. It aims to provide a bridge between genomic data and proteomic studies, allowing users to explore molecular functional characteristics of crVARs and proteins bearing these variations, i.e., cancer-related proteins.
The database comprises a compilation of mutated peptides identified in cancerous samples. Open in Notepad and save with a .fasta extension. The applicability of the database to identifying the presence of mutated peptides was investigated with MCF-7 breast cancer cell extracts.
An integrated genomics and proteomics strategy (referred to iMASp - identification of Mutated And Secreted proteins) identify 112 putative mutated tryptic peptides (corresponding to 57 proteins) in the collective secretomes derived from a panel of 18 human colorectal cancer (CRC) cell lines. Central to this iMASp was the creation of Human Protein Mutant Database (HPMD), against which experimentally-derived secretome peptide spectra were searched.
A database of mutagenesis and mutation information on Human Immunodefiency Virus (HIV). Hivmut describes the phenotypes of 7,608 unique mutations at 2,520 sites in the HIV proteome, resulting from the analysis of 120,899 papers. The mutation information for each protein is organised in a residue-centric manner and each residue is linked to the relevant experimental literature. The importance of HIV as a global health burden advocates extensive effort to maximise the efficiency of HIV research. The HIV mutation browser provides a valuable new resource for the research community.
Collects information about von Hippel-Lindau protein (pVHL) interactors and mutation effects. VHLdb is both a manually and automatically curated repository that compiles more than 470 interactors and over 1000 pathogenic somatic or germline pVHL mutations. The platform allows users to browse data: (i) by interaction, providing an interactive and downloadable tree diagram; or (ii) by mutations by using a table interface that allows searches and filtering by several features such as variants, type or codon.
Consists in a 3D-structure oriented repository of protein C. ProCMD associates clinical and phenotypical descriptions with functional and structural data obtained by computational approaches. Users can retrieve entries by the position in the sequence of a mutated residue, by amino acidic substitution, and by domain localization. The database can be useful to assist in prediction of the effect of a mutation, clarification of the role of specific residues in protein function.
Represents a database allowing the exploration of protein domains. Cancerouspdomains is a platform that assists users to study mutations from more than 25 cancer types to both sequence and structure-based domains. It allows users to realize a research by several ways: (1) UniProt ID, (2) HGNC IS, (3) ApprovedSymbol, (4) UCSC IS, (5) Ensembl ID, (6) RefSeq IDs.
Contains information of the phenotype of about genomic sequences of the T-DNA insertion sites and 500 morphological mutants. RIKEN Arabidopsis Activation tagging line includes more than 50,000 RIKEN Activation Tagging lines. Several mutant phenotypes are handle and store in various categories. It is possible users to search information by different classes and to download contents.
Provides a compilation of protein mutant data, providing information on functional and/or structural influences brought about by amino acid mutations at specific positions of a protein. PMD is an online resource is unique in two respects: (i) almost all proteins are included, except for natural mutants of the globin and immunoglobulin families; (ii) natural as well as artificial mutants are covered, including random and site-directed mutants.
Dr. Yashwanth Subbannayya obtained his M.Sc. degree in Medical Biochemistry from Manipal University. He qualified the competitive CSIR-UGC National Eligibility Test and joined the Institute of Bioinformatics, Bangalore as a UGC Junior Research Fellow. As part of his Ph.D. work, he studied the molecular mechanisms of gastric cancer in clinical specimens using quantitative proteomic technologies. This study, the results of which were published in Cancer Biology and Therapy, yielded a novel therapeutic target for gastric cancer- CAMKK2. Further, he also studied the serum proteome of gastric cancer patients and developed assays for potential markers using the revolutionary multiple reaction monitoring approach. The results of this study were published in Journal of Proteomics. In addition to his research work, he also trained extensively in sample preparation for mass spectrometry, fractionation techniques and gained expertise in quantitative proteomic techniques and data analysis. In addition, he also trained extensively in various validation platforms including immunohistochemsitry, multiple reaction monitoring and Western blot. He has also worked as a curator for several biological databases including NetPath, Human Protein Reference Database (HPRD) and Breast cancer database. His work in various research projects have yielded him 23 publications either as lead author or co-author in peer reviewed journals. He is a reviewer for the journal Proteomics.
Dr. Yashwanth Subbannayya joined the YU-IOB Center for Systems Biology and Molecular Medicine in June, 2015. During the initial period, his job consisted of assisting other personnel of the university in the establishment of YU-IOB Center for Systems Biology and Molecular Medicine. He was also involved in training of Ph.D. students in biological aspects. After the establishment of the center, he trained in cell culture techniques and metabolomics analysis. At YU-IOB CSBMM, he is studying the molecular mechanisms in various cancers including oral cancer. In addition, he is studying the molecular mechanisms as well as the metabolic constituents of traditional medicine formulations using mass spectrometry technologies. In June 2016, he convened the national symposium “Genomics in clinical practice: Future of precision medicine” held at Yenepoya University on June 1 and 2, 2016. The resource persons included 16 individuals from various academic organizations as well as industry. The symposium was attended by 218 participants from 24 institutions around India. He is a member of the Scientific Review Board of Yenepoya Research Centre where he facilitates timely scientific review of research projects.