Provides manually curated published data sets of large-scale subcellular proteomics, fluorescent protein visualization, protein-protein interaction (PPI) as well as subcellular targeting calls from 22 prediction programs. SUBA4 contains an additional 35 568 localizations totalling more than 60 000 experimental protein location claims as well as 37 new suborganellar localization categories. The SUBA4 user interface enables users to choose quickly from the filter categories: ‘subcellular location’, ‘protein properties’, ‘protein-protein interaction’ and ‘affiliations’ to build complex queries. Furthermore, a ‘BLAST’ tab contains a sequence alignment tool to enable a sequence fragment from any species to find the closest match in Arabidopsis and retrieve data on subcellular location. Finally, using the location consensus SUBAcon, the SUBA4 toolbox delivers three novel data services allowing interactive analysis of user data to provide relative compartmental protein abundances and proximity relationship analysis of PPI and coexpression partners from a submitted list of Arabidopsis gene identifiers.
A web-accessible database of protein subcellular localization (SCL) for bacteria that contains both information determined through laboratory experimentation and computational predictions. The dataset of experimentally verified information (approximately 2000 proteins) was manually curated by us and represents the largest dataset of its kind. PSORTdb will be of particular interest to researchers studying microbes outside those with the classical Gram-negative diderm and Gram-positive monoderm cell envelope structures, including medically relevant species such as Mycobacterium tuberculosis and Mycoplasma pneumoniae, agriculturally relevant species such as Spiroplasma citri and industrially relevant species such as Thermotoga maritima.
Provides integrated access to complementary DNA (cDNA)-data, experimental results and bioinformatics information. LIFEdb is a database enabling researchers to systematically select and characterize genes and proteins of interest. The database was developed to publish data on full-length cDNAs and the subcellular localization of the encoded proteins.
A database for proteins temporally and spatially localized in distinct subcellular positions including midbody, centrosome, kinetochore, telomere and mitotic spindle during cell division/mitosis. MiCroKiTS can serve as a useful resource for further analyzing the molecular mechanisms during cell division.
Offers a database that regards nuclear localization signals (NLSs) and proteins translocated into the nucleus by signal sequences. NLSdb is a comprehensive source of information that can be easily integrated with other public and proprietary databases. NLSdb can greatly help in better understanding signal dependent nuclear transport of proteins. It contains over 6000 predicted nuclear proteins and their targeting signals from the protein database (PDB) and SWISS-PROT/TrEMBL databases.
Holds information about the protein names, their organism and the cell-type. NMP-db provides a database with proteins associated to the nuclear matrix. This database can be accessed from a search-engine interface that allows the querying by different database fields and the linking of queries through ‘AND’, ‘OR’ and ‘AND-NOT’. It also links to the respective PubMed abstracts that are given in each entry.
Supports functional Listeria genome analyses by combining information obtained by applying bioinformatics methods and from public databases to improve the original annotations. LEGER offers three unique key features: (i) it is the first comprehensive information system focusing on the functional assignment of genes and proteins; (ii) integrated visualization tools, KEGG pathway and Genome Viewer, alleviate the functional exploration of complex data; and (iii) LEGER presents results of systematic post-genome studies, thus facilitating analyses combining computational and experimental results.
Maps validated gene and protein expression, phenotype and images related to cell types. The data allow characterization and comparison of cell types and can be browsed by using the body browser and by searching for cells or genes. All cells are related to more complex systems such as tissues, organs and organisms and arranged according to their position in development. CellFinder provides long-term data storage for validated and curated primary research data and provides additional expert-validation through relevant information extracted from text.
An online resource for Caulobacter studies. CauloBrowser provides a user-friendly interface for quickly searching genes of interest and downloading genome-wide results. Search results about individual genes are displayed as tables, graphs of time resolved expression profiles, and schematics of protein localization throughout the cell cycle. In addition, the site provides a genome viewer that enables customizable visualization of all published high-throughput genomic data. The depth and diversity of data sets collected by the Caulobacter community makes CauloBrowser a unique and valuable systems biology resource.
Provides gene ontology (GO) and subcellular localization annotations. PA-GOSUB offers search and browsing capabilities that add query functionality to the pre-computed model organisms. It contains more than 140 000 proteins, about 27 000 Gene Ontology Annotation (GOA) and more than 100 000 Proteome Analyst (PA) for Gene Ontology (GO) molecular function. The database can be used to assist users to understand why a classifier makes a particular classification thank to the implementation of an explanation mechanism.
A cellular compartment-specific database of proteins and their interactions enabling an extensive, compartmentalized protein-protein interaction network analysis. ComPPI enables the user to filter biologically unlikely interactions, where the two interacting proteins have no common subcellular localizations and to predict novel properties, such as compartment-specific biological functions. ComPPI is an integrated database covering four species (S. cerevisiae, C. elegans, D. melanogaster and H. sapiens).
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.
An improved and updated version of the fungal secretome and subcellular proteome, i. e. protein subcellular location, knowledgebase. The fungal protein sequence data were retrieved from UniProtKB, consisting of nearly 2 million entries with 167 species having a complete proteome. The assignments of protein subcellular locations were based on curated information and prediction using seven computational tools. The tools used for subcellular location prediction include SignalP, WoLF PSORT, Phobius, TargetP, TMHMM, FragAnchor, and PS-Scan. Secreted proteins, i.e. secretomes, along with 15 other subcellular proteomes were predicted. FunSecKB can be searched by users using several different types of identifiers, gene name or keyword(s). A subcellular proteome from a species can be searched or downloaded. BLAST searching whole fungal protein data or secretomes is available.
Collates more than 550 data sets from previously published fluorescent tagging or mass spectrometry studies and eight pre-computed subcellular predictions for barley, wheat, rice and maize proteomes. The data collection including metadata for proteins and studies can be accessed through the search portal. The reciprocal blast and EnsemblPLants homology tree allows the search for location data across the four crop species as well as compares it to Arabidopsis data from SUBA. The subcellular localization information housed in cropPAL helps to depict plant cells as compartmentalized protein networks that can be investigated for improving crop yield and quality, and developing new biotechnological solutions to agricultural challenges.
Provides access to information on tagged lines for nuclear-encoded chloroplast proteins, including their phenotypes and genotypes. The Chloroplast Function Database is a publicly available web-based resource that offers significant improvements in usability. It also provides additional important information to the plant biology community, enabling searches for visible phenotypes of genes of interest.
A public database, developed to organize a large data set of confocal images generated from the maize marker lines, for studying native gene expression in specific cell types and subcellular compartments using fluorescent proteins. Maize Cell Genomics Database represents two types of data: (i) information which describes fluorescent-tagged gene constructs used for maize marker line generation; and (ii) confocal images representing spatial and temporal expression of the fluorescent markers in the maize marker lines.
Provides a central platform for housing and analyzing our yeast proteome dynamics datasets at the single cell level. CYCLoPs differs from existing databases in a number of ways: (1) whereas other databases provide searchable localization assignments for proteins that had been assessed visually, CYCLoPs contains computationally derived quantitative localization and abundance profiles; (2) CYCLoPs provides a searchable web graphical interface for proteins with localization and/or abundance changes of interest, which reflects the proteome flux in response to varying environmental cues and genetic backgrounds; (3) the subcellular localization data hosted on CYCLoPs were determined directly from the morphologic features of the cells and accommodate the reality that many proteins localize to multiple locations; and (4) CYCLoPs provides localization and abundance profiles for individual cells screened, thus enabling analysis at the single-cell level.
A secretome and subcellular proteome knowledgebase specifically designed for metazoan, i.e. human and animals. The protein sequence data, consisting of over 4 million entries with 121 species having a complete proteome, were retrieved from UniProtKB. Protein subcellular locations including secreted and 15 other subcellular locations were assigned based on either curated experimental evidence or prediction using seven computational tools. The protein or subcellular proteome data can be searched and downloaded using several different types of identifiers, gene name or keyword(s), and species. BLAST search and community annotation of subcellular locations are also supported.
A manually curated database of experimental protein localization signals for eight distinct subcellular locations; primarily in a eukaryotic cell with brief coverage of bacterial proteins. From LocSigDB webserver, users can download the whole database or browse/search for data using an intuitive query interface. To date, LocSigDB is the most comprehensive compendium of protein localization signals for eight distinct subcellular locations.
A database for the plant research community to access and curate plant protein subcellular locations, with a focus on secreted proteins. PlantSecKB is constructed with all the available plant protein data retrieved from the UniProtKB database and plant protein sequences predicted from EST data assembled by the PlantGDB project. The database contains information collected from three sources: (1) subcellular locations that were curated or computationally predicted in the UniProtKB; (2) subcellular locations and features predicted by eight computational tools; (3) secreted proteins that were curated from recent literature.
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.
Provides subcellular localization data for over 6000 rat liver proteins. Prolocate offers the ability to query subcellular distribution of individual proteins and examine underlying data, compile lists of candidate residents of different organelles, and identify proteins with similar multi-compartmental distributions. The database allows inspection of the fractionation profiles of all component peptides assigned to each protein.
Provides a comprehensive and quantitative 4D model of the mitotic protein localization network in a dividing human cell. Mitotic Cell Atlas is an integrated experimental and computational framework that provides a standardized yet dynamic spatio-temporal reference system for the mitotic cell. It can be used to integrate quantitative information on any number of protein distributions sampled in thousands of different experiments.
Offers a database of predictions for Endoplasmic Reticulum (ER) and Golgi Apparatus localization. ER-GolgiDB is a comprehensive source of information based on sequence homology to experimentally annotated proteins. ER and Golgi localization is predicted using the explicit "Accuracy versus Scaled HSSP distance" curves for each localization. The assigned localization is inferred from the homologue that most accurately predicts localization for the protein and the accuracy based on HSSP distance threshold is provided.
A knowledgebase for protist secretomes as well as protist proteins located in other subcellular locations. Protein sequences are obtained from UniProtKB. Subcellular locations are identified using curated annotation combined with predictions from several publicly available computational tools. ProtSecKB contains data for 954,378 proteins obtained from UniProtKB August, 2014.
Offers user a list of each protein's spacio-temporal localization images. 3DPL provides different types of information such as developmental stage, experimental condition, cellular localization or staining method. It’s a useful resource for better understanding proteins functions.
A database of protein subcellular localization. This database contains proteins from primary protein database SWISS-PROT and PIR. By collecting the subcellular localization annotation, these information are classified and categorized by cross referencs to taxonomies and Gene Ontology database.
Enables biochemical researchers to quickly access summarized subcellular localization of pathways from UniProt and KEGG pathway databases. As the first effort to systematically integrate pathway localization, this database is very useful in discovering the variation of localization of pathways between organisms and also cross-talk between different organelles within a pathway.
A comprehensive database that gathers all prediction outputs concerning complete prokaryotic proteomes. CoBaltDB is a powerful platform that provides easy access to the results of multiple localization tools and support for predicting prokaryotic protein localizations with higher confidence than previously possible.
A specific database aimed at multiple localization annotated proteins. Proteins are cross-referenced to NCBI taxonomy, Gene Ontology and original database. Proteins that interact with each other tend to share the same subcellular localizations. So, protein-protein interaction information is also integrated into the database. A quality score is derived from protein-protein interactions.
Contains a comprehensive characterization of subcellular localization and topology of the complete proteome of Escherichia coli. Two widely used E. coli proteomes (K-12 and BL21) are presented organized into thirteen subcellular classes. STEPdb exploits the wealth of genetic, proteomic, biochemical, and functional information on protein localization, secretion, and targeting in E. coli, one of the best understood model organisms. Subcellular annotations were derived from a combination of bioinformatics prediction, proteomic, biochemical, functional, topological data and extensive literature re-examination that were refined through manual curation.
Performs integrated searches for functional annotations, subcellular location, expression levels, and putative or known regulatory elements, as well as showing orthologues between rice and Arabidopsis. Rice DB can reveal putative function annotations from a variety of sources, expression annotations, predicted subcellular localization, experimentally determined location as well as the phenotypes for proteins with experimentally confirmed subcellular locations, and simply link to the Arabidopsis orthologues(s).
Combines many of the existing high-precision protein subcellular-location (SCL) identifiers with our own developed identifiers for specific SCLs. The LocateP pipeline was designed such that it mimics protein targeting and secretion processes. It distinguishes 7 different SCLs within Gram-positive bacteria: intracellular, multi-transmembrane, N-terminally membrane anchored, C-terminally membrane anchored, lipid-anchored, LPxTG-type cell-wall anchored, and secreted/released proteins. Moreover, it distinguishes pathways for Sec- or Tat-dependent secretion and alternative secretion of bacteriocin-like proteins.
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.