Gathers information about the protein-coding genes of seventeen major cancer types and their genome-wide transcriptome. Pathology Atlas is an open-access database, part of the Human Protein Atlas, which aims to examine the prognostic role of each protein-coding gene in the different cancers. The database uses transcriptomics and antibody-based profiling to provide a standalone resource for cancer precision medicine.
A knowledge-based portal with gene-centric expression profiles based on the annotation of several antibodies towards the same protein target. Because all the data on the Human Protein Atlas are publicly available, the information can be integrated into other databases. The availability of the annotated expression patterns opens up the possibility for a community-based dialog to provide input by researchers with specialized knowledge about particular protein targets.
Provides information about gene and protein expression in animal and plant samples of different cell types, organism parts, developmental stages, diseases and other conditions. Expression Atlas consists of selected microarray and RNA-sequencing studies from ArrayExpress, which have been manually curated, annotated with ontology terms, checked for high quality and processed using standardised analysis methods. Expression Atlas search interface allows for querying one or more genes or proteins from a selected species. The user can also add search filters for sample attributes and experimental factors, taking full advantage of ontology-driven query expansion.
Consists of a cell type- and brain region-specific atlas of open chromatin. BOCA assists users in the investigation of the regulation of gene expression in the brain. It can serve for the study of the impact of neuropsychiatric disease risk variants. This tool furnishes maps of neuronal and non-neuronal chromatin accessibility across 14 distinct brain regions of 5 adult individuals.
An integrated web-based resource that catalogues the genomic and proteomic annotations identified in colorectal cancer (CRC) tissues and cell lines. The data catalogued to-date include sequence variations as well as quantitative and non-quantitative protein expression data. The database enables the analysis of these data in the context of signaling pathways, protein–protein interactions, Gene Ontology terms, protein domains and post-translational modifications. Currently, Colorectal Cancer Atlas contains data for >13 711 CRC tissues, >165 CRC cell lines, 62 251 protein identifications, >8.3 million MS/MS spectra, >18 410 genes with sequence variations (404 278 entries) and 351 pathways with sequence variants. Overall, Colorectal Cancer Atlas has been designed to serve as a central resource to facilitate research in CRC.
Contains easily accessible and user-friendly information about subcellular localization and levels for 5330 yeast proteins under three environmental stress conditions and two genetic perturbations. Using LoQAtE DB, users can get a profile of changes for proteins of interest as well as querying advanced intersections by either abundance changes, primary localization or localization shifts over the tested conditions. Currently, the DB hosts information on 5330 yeast proteins under three external perturbations (DTT, H2O2 and nitrogen starvation) and two genetic mutations [in the chaperonin containing TCP1 (CCT) complex and in the proteasome]. Additional conditions will be uploaded regularly. The data demonstrate hundreds of localization and abundance changes, many of which were not detected at the level of mRNA. LoQAtE is designed to allow easy navigation for non-experts in high-content microscopy and data are available for download.
Provides centralized storage and distribution for the protein expression plasmids created by PSI researchers. PSI-MR is a resource that informs about plasmids, theses plasmids permits researchers to find the biological function of protein. For each PSI plasmid, user can retrieve additional resources simplifying cross-referencing of a particular plasmid to protein annotations and experimental data.
An online resource devoted to studying the human pathogen Mycoplasma pneumoniae, a minimal bacterium causing lower respiratory tract infections. MyMpn hosts a wealth of omics-scale datasets generated by hundreds of experimental and computational analyses. These include data obtained from gene expression profiling experiments, gene essentiality studies, protein abundance profiling, protein complex analysis, metabolic reactions and network modeling, cell growth experiments, comparative genomics and 3D tomography.
Provides information about human cells. SHOGoiN Cell Database contains cell differentiation pathways compiled from biomedical textbooks and journal papers and includes its own cell classification scheme in which each human cell is classified according to physical locations. Several cell taxonomy keys exist to tidy human differentiated cells and stem cells.
Contains gene-tissue associations in human and three mammalian model organisms. TISSUES provides tissue associations protein-coding genes, collected from multiple sources and data types. It includes confidence scores for every associations to make them comparable across data sources, data types, and organisms. This database shows gene-tissue correlations between orthologous and paralogous genes, simplifying comparisons across organisms.
Allows to genetic diversity in human populations. HGDP has collected genomic DNA from 1,043 individuals from around the world and has determined their genotypes at more than 650,000 single nucleotide polymorphism (SNP) loci. It represents 51 different populations from Africa, Europe, the Middle East, South and Central Asia, East Asia, Oceania and the Americas. The database shares ancestry and admixture, relationships between haplotype heterozygosity and geography, and population differences in copy number variation (CNV) throughout the human genome in the 1,043 individuals.
Allows users to store, retrieve, and perform integrated analysis of data from high throughput proteomic technologies. YPED is a web-accessible database for managing, querying, viewing, interpreting, and archiving data derived from multiple, state of-the-art protein profiling technologies. It consists of three components: an Oracle database server, a web interface and an ftp file server. The database is designed to capture DIGE data in addition to data generated by other protein profiling techniques including MudPIT, ICAT, and iTRAQ.
A model of the molecular networks present in grapevines. VitisNet allows visualization of the dynamic interactions in the transcriptome, proteome, and metabolome within known molecular networks (for example, metabolic or signaling pathways). Integrating transcripts with protein and metabolite profiles in a comprehensive molecular map enables the researcher to elucidate different biochemical responses of grapevines to developmental and environmental cues. VitisNet uses manually annotated networks in SBML or XML format, enabling the integration of large datasets, streamlining biological functional processing, and improving the understanding of dynamic processes in systems biology experiments.
Provides easy and intuitive access to protein synthesis data derived from various proteomics experiments. Aureolib is by far the most comprehensive protein expression database for S. aureus and provides an essential tool to decipher more complex adaptation processes in S. aureus during host pathogen interaction.
A large database resource and suite of data visualization tools designed to interrogate how the abundance of proteins and their isoforms change as a function of developmental stage in Caenorhabditis elegans. All the raw data used to develop this resource are available for download.
Stores Varroa destructor life cycle proteins. Varroa protein atlas cross all major developmental stages (egg, protonymph, deutonymph and adult) for both male and female mites as a web-based interactive tool. The atlas was built using the framework for the honey bee protein atlas. It features a searchable database of the quantified proteins as well as a visual and numerical display of their relative expression in different developmental stages.
A community portal for sharing and integration of human protein data. It allows research laboratories to contribute and maintain protein annotations. Human Protein Reference Database (HPRD) integrates data, that is deposited in Human Proteinpedia along with the existing literature curated information in the context of an individual protein. All the public data contributed to Human Proteinpedia can be queried, viewed and downloaded.
A non-redundant, curated database of human RNA binding proteins (RBPs). RBPs curated from different experimental studies are reported with their annotation, tissue-wide RNA and protein expression levels, evolutionary conservation, disease associations, protein-protein interactions, microRNA predictions, their known RNA recognition sequence motifs as well as predicted binding targets and associated functional themes, providing a one stop portal for understanding the expression, evolutionary trajectories and disease dynamics of RBPs in the context of post-transcriptional regulatory networks.
Contains information about fly named Drosphila melanogaster. JDD offers users the possibility to search information by genes and phenotypes, anatomical terms, or taxonomy. This database also assists user in consultation of chromosomal maps or proteome atlas.
Provides a repository for multi-omics data of human and model organisms. MOPED uses a pathway-centric view to integrate protein and gene expression data. It can assist researchers to: (1) detect potential proteins to study based on expression levels, (2) compare expression of different proteins across experiments, conditions localization and tissues, (3) search expression levels in several tissue types, cell lines, conditions and diseases and to (4) associate uncharacterized proteins to diabetes and cancer.
Contains human disease-related mutated sequences. SysPIMP comprises about 35 500 non-redundant human disease-related mutated proteins of which about 21 500 were from OMIM, 700 from PMD and 15 300 from SwissProt. The platform offers programs to identify mutated proteins from the mass spectrometry (MS) results. It is designed to provide an efficient way to search the complex data stored on database.
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.