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diff --git a/general/brand/aging/home.md b/general/brand/aging/home.md index 33c18e1..17ca578 100644 --- a/general/brand/aging/home.md +++ b/general/brand/aging/home.md @@ -1,5 +1,14 @@ -New aging portal! This is initial work for providing a full community webservice for aging. +New UMHET3 and aging portal! This is initial work for providing a full community webservice for aging. +- [https://doi.org/10.1101/2025.04.27.649857](https://doi.org/10.1101/2025.04.27.649857). +**Genetic Modulation of Lifespan: Dynamic Effects, Sex Differences, and Body Weight Trade-offs** -This is a stub until David edits it! Or Rob. See this link to [edit](https://github.com/genenetwork/gn-docs/edit/master/general/brand/aging/home.md). +> **Abstract**: The dynamics of lifespan are shaped by DNA variants that exert effects at different ages. We have mapped genetic loci that modulate age-specific mortality using an actuarial approach. We started with an initial population of 6,438 pubescent siblings and ended with a survivorship of 559 mice that lived to at least 1100 days. Twenty-nine Vita loci dynamically modulate the mean lifespan of survivorships with strong age- and sex-specific effects. Fourteen have relatively steady effects on mortality while other loci act forcefully only early or late in life and with polarities of effects that invert. A distinct set of 19 Soma loci shape the negative correlation between weights of young adults with their life expectancies—much more strongly so in males than females. Another set of 11 Soma loci shape the positive correlation between weights at older ages with life expectancies. The Vita and Soma loci share 289 age-dependent epistatic interactions (LODs ≥3.8) but fewer than 4% are common to both sexes. [More...](https://doi.org/10.1101/2025.04.27.649857). -For markdown check [the docs](https://commonmark.org/help/). To embed images you can use a link somewhere from the internet or check it into the gn-doc repo and I'll add a link. +We provide two examples of how to move from maps toward potential mechanisms. Our findings provide an empirical bridge between evolutionary theories on aging and genetic and molecular causes. These loci and their interactions are key to begin to understand the impact of interventions that may extend healthy lifespan in mice and even in humans. + + + +- Data files are available [here](https://files.genenetwork.org/current/umhet3_2025/). +- Code is available at [https://github.com/DannyArends/UM-HET3/](https://github.com/DannyArends/UM-HET3/) + +See also GeneNetwork.org [examples on aging](https://aging.genenetwork.org/). diff --git a/general/brand/aging/um-het3.png b/general/brand/aging/um-het3.png new file mode 100644 index 0000000..5c762ce --- /dev/null +++ b/general/brand/aging/um-het3.png Binary files differdiff --git a/general/brand/gnqa/gnqa.md b/general/brand/gnqa/gnqa.md new file mode 100644 index 0000000..bdd559c --- /dev/null +++ b/general/brand/gnqa/gnqa.md @@ -0,0 +1,20 @@ +# GNQA the Genenetwork.org Question Answer System + +## Purpose + +Genenetwork.org (GN) is a site housing tens of terabytes of experimental genetic and genomic information on many species, most notably mouse and human. In its constantly evolving state the masterminds behind this systems genetics service look to make it easier to use for non-experts or citizen scientists. To this end GNQA, a retrieval augmented generation service, is under development to support knowledge communication and research understanding. + +### Accessing GNQA +In order to use GNQA you must be a registered user of genenetwork.org. If you have not yet registered, do so [here](https://genenetwork.org/oauth2/user/register). +The GN registration page with have you verify the email address you used for registration. Once your email has been confirmed you can log in to genenetwork.org. +There are two ways to query GNQA: the 1st is by using the genenetwork.org global search, the 2nd is by visiting [GNQA directly](https://genenetwork.org/gnqna). +When using the global search, GNQA results are presented in a small panel above the table of records. + + + +## Knowledge Communication & Research Understanding + +GNQA is a tool utilizing a large language model and a separately maintained scientific knowledge base with specially and specifically curated data. The curated data is currently focused on three main areas: GN research, genomics of aging, and the genomics of diabetes. We chose each area based on our research interests. GNQA as it currently exists, as of 16 January 2025, is comprised of 3000 research tomes in our listed areas of interest. The GN global search bar returns a table of often several thousand results and links to datasets related to ones query, whereas GNQA queries its knowledge base of research documents and books to return an answer to the query along with a list of references, real... not hallucinated. Some references are presented with links to the research documents on [PubMed](https://www.ncbi.nlm.nih.gov/pubmed "The destination for science research"). + +### System Workflow + diff --git a/general/brand/gnqa/imgs/integration.png b/general/brand/gnqa/imgs/integration.png new file mode 100644 index 0000000..d08039f --- /dev/null +++ b/general/brand/gnqa/imgs/integration.png Binary files differdiff --git a/general/brand/gnqa/imgs/pubmed-ref.png b/general/brand/gnqa/imgs/pubmed-ref.png new file mode 100644 index 0000000..8e72933 --- /dev/null +++ b/general/brand/gnqa/imgs/pubmed-ref.png Binary files differdiff --git a/general/brand/gnqa/imgs/refs.png b/general/brand/gnqa/imgs/refs.png new file mode 100644 index 0000000..819da62 --- /dev/null +++ b/general/brand/gnqa/imgs/refs.png Binary files differdiff --git a/general/brand/gnqa/imgs/workflow.png b/general/brand/gnqa/imgs/workflow.png new file mode 100644 index 0000000..fdc9916 --- /dev/null +++ b/general/brand/gnqa/imgs/workflow.png Binary files differdiff --git a/rdf-documentation/phenotype-metadata.md b/rdf-documentation/phenotype-metadata.md index a6e6c02..fe00b4e 100644 --- a/rdf-documentation/phenotype-metadata.md +++ b/rdf-documentation/phenotype-metadata.md @@ -14,7 +14,6 @@ The above query results to triples that have the form: ```text gn:traitPhenotype -> rdf:type -> gnc:Phenotype gn:traitPhenotype -> gnt:belongsToGroup -> gn:setInbredset_inbredsetname -gn:traitPhenotype -> rdfs:label -> PublishXRef(Id) gn:traitPhenotype -> skos:altLabel -> Phenotype gn:traitPhenotype -> dct:description -> PhenotypePost_publication_description gn:traitPhenotype -> gnt:abbreviation -> Phenotype(Post_publication_abbreviation) @@ -48,7 +47,6 @@ PREFIX pubmed: <http://rdf.ncbi.nlm.nih.gov/pubmed/> SELECT * WHERE { ?s rdf:type gnc:Phenotype . ?s gnt:belongsToGroup gn:setBxd . - ?s rdfs:label "10001" . ?s skos:altLabel "BXD_10001" . ?s ?p ?o . } |
