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LAMHDI, the initiative to Link Animal Models to Human DIsease, is designed to accelerate the research process by providing biomedical researchers with a simple, comprehensive Web-based resource to find the best animal models for their research. LAMHDI is funded by the National Institutes of Health under a contract managed by the National Center for Research Resources.
LAMHDI includes mouse data from MGI, the Mouse Genome Informatics website; zebrafish data from ZFIN, the Zebrafish Model Organism Database; rat data from RGD, the Rat Genome Database; yeast data from SGD, the Saccharomyces Genome Database; and fly data from FlyBase.
"LAMHDI gives biomedical researchers access to a simple yet comprehensive Web-based resource that enables scientists to quickly find the best animal models for their research studies," says Harold Watson, Ph.D., the project officer from NCRR’s Division of Comparative Medicine. "Critical tools such as these can help accelerate the research process, ultimately leading us to faster treatments."
LAMDHI is a free, Web-based, resource to help researchers bridge the gap between bench testing and human trials. It provides biomedical researchers with a simple, unbiased resource to find animal models for their research.
The LAMHDI team includes experts in scientific ontology and animal model research from the Washington National Primate Research Center at the University of Washington, the Wisconsin National Primate Research Center at the University of Wisconsin-Madison, and NeuroLex at the University of California, San Diego. TCG, a Washington D.C. project management and application development contractor, leads the initiative.
LAMHDI is operational today, with data being added regularly. Enhancements are planned to let researchers contribute their knowledge of the animal models available through LAMHDI. The LAMHDI goal is to allow researchers to share information about and access to animal models so they can refine research and testing, and reduce or replace the use of animal models where possible.
LAMHDI Database Search
LAMHDI brings together scientifically validated information from various sources to create a composite multi-species database of animal models of human disease. To do this, the LAMHDI database is prepared from a variety of sources.
Some sources are curatorial: The LAMHDI team takes publicly available data from OMIM, NCBI's Entrez Gene database, Homologene, and WikiPathways, and builds a mathematical graph (think of it as a map or a web) that links these data together. We use OMIM to link human diseases with specific human genes. We use Entrez for universal identifiers for each of those genes. We link human genes to their counterpart genes in other species using Homologene, and we link those genes to other genes that are tentatively or authoritatively linked with them in some way using the data in WikiPathways.
This preparatory work gives LAMHDI a web of human diseases linked to specific human genes, orthologous human genes, homologous genes in other species, and both human and non-human genes involved in specific metabolic pathways associated with those diseases.
Some sources provide the model information: LAMHDI includes model data that partners share with us, which is plugged into our data structure. For instance, MGI provides information about mouse models, including a disease for each model, as well as a bit of genetic information (the ID of the model, in fact, identifies one or more genes); while ZFIN provides genetic information for each zebrafish model, but no diseases. We plug each zebrafish model into our database using the genes as the glue. For instance, a hypothetical zebrafish that involves the zebrafish PKD2 gene would plug into the larger disease-gene map at the node representing the zebrafish PKD2 gene, which is connected to the node representing the human PKD2 gene, which in turn is connected to the node representing the human disease known as polycystic kidney disease. (Some of the partner data we receive can even extend our base map. MGI provides a disease for every model, and in some cases this allows us to create a disease-to-gene relationship in our database that might not already be documented in the OMIM dataset.)
With our curatorial and model information in hand, we run a lengthy automated process that exhaustively searches for every possible path between each model and each disease in the data, up to some arbitrary number of hops (producing for each disease-to-model pair a set of links from the disease to the model). The algorithm avoids circular paths and paths that include more than one disease anywhere in the middle of the path. At the end of this phase, LAMHDI has a comprehensive set of paths representing all the disease-to-model relationships in our data, varying in length from one hop to many hops. Each disease-to-model path is essentially a string of nodes in our data, where each node represents a disease, a gene, a linkage between genes (an orthologue, a homologue, or a pathway connection, referred to as a gene cluster or association), or a model. Each node has a human-friendly label, a set of terms and keywords, and — in most cases — a URL linking the node to the data source where it originated. We're now ready for our users.
When a researcher submits a search on the LAMHDI website, LAMHDI searches for the user's search terms in its precomputed list of all known disease-to-model paths (looking for the terms not only in the disease and model nodes, but also every node along each path). The complete set of hits may include multiple paths between any given disease-to-model pair of endpoints. Each of these disease-to-model pair sets is ordered by the number of hops it involves, and the one involving the fewest hops is chosen to represent its respective disease-to-model pair in the search results presented to the user (which are sorted overall by their search term matching scores).
The number of hops is one barometer of the strength of the evidence linking the model and the disease; fewer hops indicates the relationship is stronger, more hops indicates it may be weaker. Note that this indicator works best for comparing models from a single partner dataset: MGI explicitly identifies a disease for each mouse model, so there can be disease-to-model hits for mice that involve just one hop. Because ZFIN does not explicitly identify a disease for each model, no zebrafish model will involve fewer than four hops to the nearest disease: from the zebrafish model to a zebrafish gene to a gene cluster to a human gene to a human disease.
Joining LAMHDI as a Partner Site
Institutions and organizations with databases about animal models of human disease are welcome to join LAMHDI as partner sites. By opening their databases to LAMHDI searches, they can advance health research, allowing scientists to delve deeper into the biologic networks and pathways that define human disease.
LAMHDI Web Search Seeds
LAMHDI web search seeds (also called "resource seeds" or simply "seeds") are starting pages from which we scan the Internet for appropriate pages for LAMHDI Web Search results. We go to every page that has a link on every starting page, and then to all the pages identified in the referenced pages to find the search term. Our searches thus bring back dozens of hits from each "seed" page.
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—Adapted from the National Institutes of Health website
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