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Found 13 result(s)
The tree of life links all biodiversity through a shared evolutionary history. This project will produce the first online, comprehensive first-draft tree of all 1.8 million named species, accessible to both the public and scientific communities. Assembly of the tree will incorporate previously-published results, with strong collaborations between computational and empirical biologists to develop, test and improve methods of data synthesis. This initial tree of life will not be static; instead, we will develop tools for scientists to update and revise the tree as new data come in. Early release of the tree and tools will motivate data sharing and facilitate ongoing synthesis of knowledge.
OrthoMCL is a genome-scale algorithm for grouping orthologous protein sequences. It provides not only groups shared by two or more species/genomes, but also groups representing species-specific gene expansion families. So it serves as an important utility for automated eukaryotic genome annotation. OrthoMCL starts with reciprocal best hits within each genome as potential in-paralog/recent paralog pairs and reciprocal best hits across any two genomes as potential ortholog pairs. Related proteins are interlinked in a similarity graph. Then MCL (Markov Clustering algorithm,Van Dongen 2000; www.micans.org/mcl) is invoked to split mega-clusters. This process is analogous to the manual review in COG construction. MCL clustering is based on weights between each pair of proteins, so to correct for differences in evolutionary distance the weights are normalized before running MCL.
METLIN represents the largest MS/MS collection of data with the database generated at multiple collision energies and in positive and negative ionization modes. The data is generated on multiple instrument types including SCIEX, Agilent, Bruker and Waters QTOF mass spectrometers.
As with most biomedical databases, the first step is to identify relevant data from the research community. The Monarch Initiative is focused primarily on phenotype-related resources. We bring in data associated with those phenotypes so that our users can begin to make connections among other biological entities of interest. We import data from a variety of data sources. With many resources integrated into a single database, we can join across the various data sources to produce integrated views. We have started with the big players including ClinVar and OMIM, but are equally interested in boutique databases. You can learn more about the sources of data that populate our system from our data sources page https://monarchinitiative.org/about/sources.
This database serves forest tree scientists by providing online access to hardwood tree genomic and genetic data, including assembled reference genomes, transcriptomes, and genetic mapping information. The web site also provides access to tools for mining and visualization of these data sets, including BLAST for comparing sequences, Jbrowse for browsing genomes, Apollo for community annotation and Expression Analysis to build gene expression heatmaps.
>>>!!!<<< as stated 2017-06-09 MPIDB is no longer available under URL http://www.jcvi.org/mpidb/about.php >>>!!!<<< The microbial protein interaction database (MPIDB) aims to collect and provide all known physical microbial interactions. Currently, 24,295 experimentally determined interactions among proteins of 250 bacterial species/strains can be browsed and downloaded. These microbial interactions have been manually curated from the literature or imported from other databases (IntAct, DIP, BIND, MINT) and are linked to 26,578 experimental evidences (PubMed ID, PSI-MI methods). In contrast to these databases, interactions in MPIDB are further supported by 68,346 additional evidences based on interaction conservation, protein complex membership, and 3D domain contacts (iPfam, 3did). We do not include (spoke/matrix) binary interactions infered from pull-down experiments.
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.
The GenitoUrinary Development Molecular Anatomy Project (GUDMAP) is a consortium of laboratories working to provide the scientific and medical community with tools to facilitate research. The key components are: (1) a molecular atlas of gene expression for the developing organs of the GenitoUrinary (GU) tract; (2) a high resolution molecular anatomy that highlights development of the GU system; (3) mouse strains to facilitate developmental and functional studies within the GU system; (4) tutorials describing GU organogenesis; and (5) rapid access to primary data via the GUDMAP database.
The Restriction Enzyme Database is a collection of information about restriction enzymes, methylases, the microorganisms from which they have been isolated, recognition sequences, cleavage sites, methylation specificity, the commercial availability of the enzymes, and references - both published and unpublished observations (dating back to 1952). REBASE is updated daily and is constantly expanding.
<<<!!!<<< As of Aug. 15, 2019, we are suspending plasmid distribution from the collection. If you would like to request BioPlex ORF clones (Harper lab) or if you identify other clones in our collection for which you cannot find an alternative, please email us at plasmidhelp@hms.harvard.edu. >>>!!!>>>