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Found 30 result(s)
The goal of the Signaling Pathways Project knowledgebase is to allow bench researchers to routinely ask sophisticated questions of the universe of multi-omics data points generated by the cellular signaling community. SPP is dedicated to helping researchers to make sense of the often overwhelming volume of multi-omics information in the field of cellular signaling.
PathCards is an integrated database of human biological pathways and their annotations. Human pathways were clustered into SuperPaths based on gene content similarity. Each PathCard provides information on one SuperPath which represents one or more human pathways.
<<<!!!<<< This repository is no longer available. >>>!!!>>> NetPath is currently one of the largest open-source repository of human signaling pathways that is all set to become a community standard to meet the challenges in functional genomics and systems biology. Signaling networks are the key to deciphering many of the complex networks that govern the machinery inside the cell. Several signaling molecules play an important role in disease processes that are a direct result of their altered functioning and are now recognized as potential therapeutic targets. Understanding how to restore the proper functioning of these pathways that have become deregulated in disease, is needed for accelerating biomedical research. This resource is aimed at demystifying the biological pathways and highlights the key relationships and connections between them. Apart from this, pathways provide a way of reducing the dimensionality of high throughput data, by grouping thousands of genes, proteins and metabolites at functional level into just several hundreds of pathways for an experiment. Identifying the active pathways that differ between two conditions can have more explanatory power than just a simple list of differentially expressed genes and proteins.
MetaCyc is a curated database of experimentally elucidated metabolic pathways from all domains of life. MetaCyc contains pathways involved in both primary and secondary metabolism, as well as associated metabolites, reactions, enzymes, and genes. The goal of MetaCyc is to catalog the universe of metabolism by storing a representative sample of each experimentally elucidated pathway. MetaCyc applications include: Online encyclopedia of metabolism, Prediction of metabolic pathways in sequenced genomes, Support metabolic engineering via enzyme database, Metabolite database aids. metabolomics research.
Pathway Commons is a convenient point of access to biological pathway information collected from public pathway databases. Information is sourced from public pathway databases and is readily searched, visualized, and downloaded. The data is freely available under the license terms of each contributing database.
The BioCyc database collection of Pathway/Genome Databases (PGDBs) provides a reference on the genomes and metabolic pathways of thousands of sequenced organisms. BioCyc PGDBs are generated by software that predict the metabolic pathways of completely sequenced organisms, predict which genes code for missing enzymes in metabolic pathways, and predict operons. BioCyc also integrates information from other bioinformatics databases, such as protein feature and Gene Ontology information from UniProt. The BioCyc website provides a suite of software tools for database searching and visualization, for omics data analysis, and for comparative genomics and comparative pathway questions. From 2016 on, access to the EcoCyc and MetaCyc databases will remain free. Subscriptions to the other 7,600 BioCyc databases will be available to institutions (e.g., libraries), and to individuals. Access to licensed databases via: https://biocyc.org/Product-summary.shtml.
WikiPathways was established to facilitate the contribution and maintenance of pathway information by the biology community. WikiPathways is an open, collaborative platform dedicated to the curation of biological pathways. WikiPathways thus presents a new model for pathway databases that enhances and complements ongoing efforts, such as KEGG, Reactome and Pathway Commons. Building on the same MediaWiki software that powers Wikipedia, we added a custom graphical pathway editing tool and integrated databases covering major gene, protein, and small-molecule systems. The familiar web-based format of WikiPathways greatly reduces the barrier to participate in pathway curation. More importantly, the open, public approach of WikiPathways allows for broader participation by the entire community, ranging from students to senior experts in each field. This approach also shifts the bulk of peer review, editorial curation, and maintenance to the community.
Tthe Lipidomics Gateway - a free, comprehensive website for researchers interested in lipid biology, provided by the LIPID MAPS (Lipid Metabolites and Pathways Strategy) Consortium. The LIPID MAPS Lipidomics Gateway provides a rich collection of information and resources to help you stay abreast of the latest developments in this rapidly expanding field. LIPID Metabolites And Pathways Strategy (LIPID MAPS®) is a multi-institutional effort created in 2003 to identify and quantitate, using a systems biology approach and sophisticated mass spectrometers, all of the major — and many minor — lipid species in mammalian cells, as well as to quantitate the changes in these species in response to perturbation. The ultimate goal of our research is to better understand lipid metabolism and the active role lipids play in diabetes, stroke, cancer, arthritis, Alzheimer's and other lipid-based diseases in order to facilitate development of more effective treatments. Since our inception, we have made great strides toward defining the "lipidome" (an inventory of the thousands of individual lipid molecular species) in the mouse macrophage. We have also worked to make lipid analysis easier and more accessible for the broader scientific community and to advance a robust research infrastructure for the international research community. We share new lipidomics findings and methods, hold annual meetings open to all interested investigators, and are exploring joint efforts to extend the use of these powerful new methods to new applications
PharmGKB is a comprehensive resource that curates knowledge about the impact of genetic variation on drug response for clinicians and researchers. PharmGKB brings together the relevant data in a single place and adds value by combining disparate data on the same relationship, making it easier to search and easier to view the key aspects and by interpreting the data.PharmGKB provide clinical interpretations of this data, curated pathways and VIP summaries which are not found elsewhere.
<<<!!!<<< The NCBI BioSystems Database will be retired in March 2022. >>>!!!>>> This retirement includes the representation of BioSystems records in the NCBI Entrez system and viewers of BioSystems content. NCBI now provides metabolic pathway and other biosystems data through the regularly updated PubChem Pathways resource (https://pubchemdocs.ncbi.nlm.nih.gov/pathways) that offers a fresh, extended, and more modern interface.
The Project on Human Development in Chicago Neighborhoods (PHDCN) is a large-scale, interdisciplinary study of how families, schools, and neighborhoods affect child and adolescent development. It was designed to advance the understanding of the developmental pathways of both positive and negative human social behaviors. In particular, the project examined the causes and pathways of juvenile delinquency, adult crime, substance abuse, and violence. At the same time, the project also provided a detailed look at the environments in which these social behaviors take place by collecting substantial amounts of data about urban Chicago, including its people, institutions, and resources. Nearly all PHDCN data require an individual application with supporting materials to obtain the data. Applications are handled by the the National Archive of Criminal Justice Data (NACJD). Further instructions will appear on the study home page (linked from search results), where relevant.
The Department of Energy Systems Biology Knowledgebase (KBase) is a software and data platform designed to meet the grand challenge of systems biology: predicting and designing biological function. KBase integrates data and tools in a unified graphical interface so users do not need to access them from numerous sources or learn multiple systems in order to create and run sophisticated systems biology workflows. Users can perform large-scale analyses and combine multiple lines of evidence to model plant and microbial physiology and community dynamics. KBase is the first large-scale bioinformatics system that enables users to upload their own data, analyze it (along with collaborator and public data), build increasingly realistic models, and share and publish their workflows and conclusions. KBase aims to provide a knowledgebase: an integrated environment where knowledge and insights are created and multiplied.
HumanCyc provides an encyclopedic reference on human metabolic pathways. It provides a zoomable human metabolic map diagram, and it has been used to generate a steady-state quantitative model of human metabolism. 2016: Subscriptions are now required to access HumanCyc. For more information on obtaining a subscription, click here: http://www.phoenixbioinformatics.org/biocyc#product-biocyc-subscription
The eyeGENE® Research Resource is open for approved research studies. Application details here Researchers and clinicians are actively developing gene-based therapies to treat ophthalmic genetic diseases that were once considered untreatable.
The Plant Metabolic Network (PMN) provides a broad network of plant metabolic pathway databases that contain curated information from the literature and computational analyses about the genes, enzymes, compounds, reactions, and pathways involved in primary and secondary metabolism in plants. The PMN currently houses one multi-species reference database called PlantCyc and 22 species/taxon-specific databases.
CryptoDB is an integrated genomic and functional genomic database for the parasite Cryptosporidium and other related genera. CryptoDB integrates whole genome sequence and annotation along with experimental data and environmental isolate sequences provided by community researchers. The database includes supplemental bioinformatics analyses and a web interface for data-mining.
FungiDB belongs to the EuPathDB family of databases and is an integrated genomic and functional genomic database for the kingdom Fungi. FungiDB was first released in early 2011 as a collaborative project between EuPathDB and the group of Jason Stajich (University of California, Riverside). At the end of 2015, FungiDB was integrated into the EuPathDB bioinformatic resource center. FungiDB integrates whole genome sequence and annotation and also includes experimental and environmental isolate sequence data. The database includes comparative genomics, analysis of gene expression, and supplemental bioinformatics analyses and a web interface for data-mining.
Reactome is a manually curated, peer-reviewed pathway database, annotated by expert biologists and cross-referenced to bioinformatics databases. Its aim is to share information in the visual representations of biological pathways in a computationally accessible format. Pathway annotations are authored by expert biologists, in collaboration with Reactome editorial staff and cross-referenced to many bioinformatics databases. These include NCBI Gene, Ensembl and UniProt databases, the UCSC and HapMap Genome Browsers, the KEGG Compound and ChEBI small molecule databases, PubMed, and Gene Ontology.
AceView provides a curated, comprehensive and non-redundant sequence representation of all public mRNA sequences (mRNAs from GenBank or RefSeq, and single pass cDNA sequences from dbEST and Trace). These experimental cDNA sequences are first co-aligned on the genome then clustered into a minimal number of alternative transcript variants and grouped into genes. Using exhaustively and with high quality standards the available cDNA sequences evidences the beauty and complexity of mammals’ transcriptome, and the relative simplicity of the nematode and plant transcriptomes. Genes are classified according to their inferred coding potential; many presumably non-coding genes are discovered. Genes are named by Entrez Gene names when available, else by AceView gene names, stable from release to release. Alternative features (promoters, introns and exons, polyadenylation signals) and coding potential, including motifs, domains, and homologies are annotated in depth; tissues where expression has been observed are listed in order of representation; diseases, phenotypes, pathways, functions, localization or interactions are annotated by mining selected sources, in particular PubMed, GAD and Entrez Gene, and also by performing manual annotation, especially in the worm. In this way, both the anatomy and physiology of the experimentally cDNA supported human, mouse and nematode genes are thoroughly annotated.
TriTrypDB is an integrated genomic and functional genomic database for pathogens of the family Trypanosomatidae, including organisms in both Leishmania and Trypanosoma genera. TriTrypDB and its continued development are possible through the collaborative efforts between EuPathDB, GeneDB and colleagues at the Seattle Biomedical Research Institute (SBRI).
Giardia lamblia is a significant, environmentally transmitted, human pathogen and an amitochondriate protist. It is a major contributor to the enormous worldwide burden of human diarrheal diseases, yet the basic biology of this parasite is not well understood. No virulence factor has been identified. The Giardia lamblia genome contains only 12 million base pairs distributed onto five chromosomes. Its analysis promises to provide insights about the origins of nuclear genome organization, the metabolic pathways used by parasitic protists, and the cellular biology of host interaction and avoidance of host immune systems. Since the divergence of Giardia lamblia lies close to the transition between eukaryotes and prokaryotes in universal ribosomal RNA phylogenies, it is a valuable, if not unique, model for gaining basic insights into genetic innovations that led to formation of eukaryotic cells. In evolutionary terms, the divergence of this organism is at least twice as ancient as the common ancestor for yeast and man. A detailed study of its genome will provide insights into an early evolutionary stage of eukaryotic chromosome organization as well as other aspects of the prokaryotic / eukaryotic divergence.