The availability of genetic variants, together with phenotypic annotations from model organisms, facilitates comparing these variants with equivalent variants in humans. However, existing databases and search tools do not make it easy to scan for equivalent variants, namely “orthologous variants,” between humans and other organisms. Therefore, we developed an integrated search engine called ConVarT (http://www.convart.org/) for orthologous variants between humans, mice, and C. elegans. ConVarT incorporates annotations (including phenotypic and pathogenic) into variants, and these previously unexploited phenotypic OrthoVars from mice and C. elegans can give clues about the functional consequence of human genetic variants. Our analysis shows that many phenotypic variants in different genes from mice and C. elegans, so far, have no counterparts in humans, and thus, can be useful resources when evaluating a relationship between a new human mutation and a disease.

In any discipline, examples are indispensable tools. They teach us the limits of our knowledge by showing us what is possible, and they can often illuminate the differences between concepts. The DaRT, leveraging the power of software, can do much more. Not only can we maintain an ever-growing store of examples, we can also efficiently explore them, and we can automate the process of "completing the picture" for each example. We can also smoothly track multiple citations for items in a way that books would have a hard time doing. In all, DaRT can provide a more complete, more easily searchable, and a better referenced package than a book.

BindingDB enables research by making a growing collection of high-quality, quantitative, protein-ligand binding data findable and usable. Funded by NIGMS/NIH.

GeneNet Engine is an exploratory tool to aid hypothesis and biomarker development at a systems-level for genotype-phenotype relationships. Expressed phenotypes may arise due to interactions between multiple genes in a system and effects from the surrounding environment. Therefore, a high systems-level view is needed to identify gene sets causal for a trait. The ability to predict genes that effect important traits is of great importance to agriculture and health. System biology approaches, that combine genomics, gene co-expression networks and data from genetic studies help provide a view at the systems-level of gene interactions. As co-expressed genes tend to be involved in similar processes, it is expected that co-expressed genes may work together to give rise to specific pheontypes. The network module serves as the basic unit of exploration in this site.

Validated NMR structures of proteins and nucleic acids.

IRIS provides management of, and access to, observed and derived data for the global earth science community. IRIS membership comprises virtually all US universities with research programs in seismology, and is dedicated to the operation of science facilities for the acquisition, management, and distribution of seismological data. IRIS programs contribute to scholarly research, education, earthquake hazard mitigation, and verification of the Comprehensive Nuclear-Test-Ban Treaty.

The mission of BioStudies is to provide access to all the data outputs of a life sciences study from a single place, by organising links to data in other databases at EMBL-EBI or elsewhere, as well as hosting data and metadata that do not fit anywhere else. The database accepts submissions via an online tool, or in a simple tab-delimited format. BioStudies provides rich mechanisms for defining and using metadata guidelines specific for a particular data source such as a project or a community, and organises datasets in collections.

A catalog of mouse genes expressed in early embryos, embryonic and adult stem cells was assembled. The cDNA libraries are freely distributed to the research community, providing a standard platform for expression studies using microarrays.

HydroShare is a system operated by The Consortium of Universities for the Advancement of Hydrologic Science Inc. (CUAHSI) that enables users to share and publish water-related data and models in a variety of flexible formats, and to make this information available in a citable, shareable and discoverable manner. HydroShare includes a repository for data and models, and tools (web apps) that can act on content in HydroShare providing users with a gateway to high performance computing and computing in the cloud. With HydroShare you can: share data and models with colleagues; manage access to shared content; share, access, visualize, and manipulate a broad set of hydrologic data types and models; publish data and models and obtain a citable digital object identifier (DOI); aggregate resources into collections; discover and access data and models published by others; use the web services application programming interface (API) to programmatically access resources; and use integrated web applications to visualize, analyze and run models with data in HydroShare.