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Found 15 result(s)
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<<<!!!<<< 2019-12-23: the repository is offline >>>!!!>>> Introduction of genome-scale metabolic network: The completion of genome sequencing and subsequent functional annotation for a great number of species enables the reconstruction of genome-scale metabolic networks. These networks, together with in silico network analysis methods such as the constraint based methods (CBM) and graph theory methods, can provide us systems level understanding of cellular metabolism. Further more, they can be applied to many predictions of real biological application such as: gene essentiality analysis, drug target discovery and metabolic engineering
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The RAMEDIS system is a platform independent, web-based information system for rare metabolic diseases based on filed case reports. It was developed in close cooperation with clinical partners to allow them to collect information on rare metabolic diseases with extensive details, e.g. about occurring symptoms, laboratory findings, therapy and molecular data.
MetaboLights is a database for Metabolomics experiments and derived information. The database is cross-species, cross-technique and covers metabolite structures and their reference spectra as well as their biological roles, locations and concentrations, and experimental data from metabolic experiments.
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.
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.
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The Small Molecule Pathway Database (SMPDB) contains small molecule pathways found in humans, which are presented visually. All SMPDB pathways include information on the relevant organs, subcellular compartments, protein cofactors, protein locations, metabolite locations, chemical structures and protein quaternary structures. Accompanying data includes detailed descriptions and references, providing an overview of the pathway, condition or processes depicted in each diagram.
<<<!!!<<< This repository is no longer available. >>>!!!>>> The Diabetes Study of Northern California (DISTANCE) conducts epidemiological and health services research in diabetes among a large, multiethnic cohort of patients in a large, integrated health care delivery system.
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One of the world’s largest banks of biological, psychosocial and clinical data on people suffering from mental health problems. The Signature center systematically collects biological, psychosocial and clinical indicators from patients admitted to the psychiatric emergency and at four points throughout their journey in the hospital: upon arrival to the emergency room (state of crisis), at the end of their hospital stay, as well as at the beginning and the end of outpatient treatment. For all hospital clients who agree to participate, blood specimens are collected for the purpose of measuring metabolic, genetic, toxic and infectious biomarkers, while saliva samples are collected to measure sex hormones and hair samples are collected to measure stress hormones. Questionnaire has been selected to cover important dimensional aspects of mental illness such as Behaviour and Cognition (Psychosis, Depression, Anxiety, Impulsiveness, Aggression, Suicide, Addiction, Sleep),Socio-demographic Profile (Spiritual beliefs, Social functioning, Childhood experiences, Demographic, Family background) and Medical Data (Medication, Diagnosis, Long-term health, RAMQ data). On 2016, May there are more than 1150 participants and 400 for the longitudinal Follow-Up
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.
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CEEHRC represents a multi-stage funding commitment by the Canadian Institutes of Health Research (CIHR) and multiple Canadian and international partners. The overall aim is to position Canada at the forefront of international efforts to translate new discoveries in the field of epigenetics into improved human health. The two sites will focus on sequencing human reference epigenomes and developing new technologies and protocols; they will also serve as platforms for other CEEHRC funding initiatives, such as catalyst and team grants. The complementary reference epigenome mapping efforts of the two sites will focus on a range of common human diseases. The Vancouver group will focus on the role of epigenetics in the development of cancer, including lymphoma and cancers of the ovary, colon, breast, and thyroid. The Montreal team will focus on autoimmune / inflammatory, cardio-metabolic, and neuropsychiatric diseases, using studies of identical twins as well as animal models of human disease.
The Database explores the interactions of chemicals and proteins. It integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug-target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins.
>>>!!!<<< Sorry.we are no longer in operation >>>!!!<<< The Beta Cell Biology Consortium (BCBC) was a team science initiative that was established by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). It was initially funded in 2001 (RFA DK-01-014), and competitively continued both in 2005 (RFAs DK-01-17, DK-01-18) and in 2009 (RFA DK-09-011). Funding for the BCBC came to an end on August 1, 2015, and with it so did our ability to maintain active websites.!!! One of the many goals of the BCBC was to develop and maintain databases of useful research resources. A total of 813 different scientific resources were generated and submitted by BCBC investigators over the 14 years it existed. Information pertaining to 495 selected resources, judged to be the most scientifically-useful, has been converted into a static catalog, as shown below. In addition, the metadata for these 495 resources have been transferred to dkNET in the form of RDF descriptors, and all genomics data have been deposited to either ArrayExpress or GEO. Please direct questions or comments to the NIDDK Division of Diabetes, Endocrinology & Metabolic Diseases (DEM).
This is the KONECT project, a project in the area of network science with the goal to collect network datasets, analyse them, and make available all analyses online. KONECT stands for Koblenz Network Collection, as the project has roots at the University of Koblenz–Landau in Germany. All source code is made available as Free Software, and includes a network analysis toolbox for GNU Octave, a network extraction library, as well as code to generate these web pages, including all statistics and plots. KONECT contains over a hundred network datasets of various types, including directed, undirected, bipartite, weighted, unweighted, signed and rating networks. The networks of KONECT are collected from many diverse areas such as social networks, hyperlink networks, authorship networks, physical networks, interaction networks and communication networks. The KONECT project has developed network analysis tools which are used to compute network statistics, to draw plots and to implement various link prediction algorithms. The result of these analyses are presented on these pages. Whenever we are allowed to do so, we provide a download of the networks.