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| author | Pjotr Prins | 2024-06-23 04:43:24 -0500 |
|---|---|---|
| committer | Pjotr Prins | 2024-06-23 04:43:24 -0500 |
| commit | 97af162af765354ac12f8013a8b31136bf3f5487 (patch) | |
| tree | 79448e8f1dac523a5510b9b3ebfa8d20eaa6e43a /templates/index.html | |
| parent | 753e43601a76f95d03e28c8d3a81d6bc2eb602be (diff) | |
| download | genecup-97af162af765354ac12f8013a8b31136bf3f5487.tar.gz | |
Simplify main page
Diffstat (limited to 'templates/index.html')
| -rw-r--r-- | templates/index.html | 13 |
1 files changed, 6 insertions, 7 deletions
diff --git a/templates/index.html b/templates/index.html index 526820b..d098324 100644 --- a/templates/index.html +++ b/templates/index.html @@ -6,24 +6,23 @@ <div class="row"> <div class="col-md-9"> - <p>GeneCup is a tool to efficiently and comprehensively answer the question <b>"What do we know about these genes and the topic I study?". + <p>GeneCup is a tool to answer the question <b>"What do we know about these genes and the topic I study?". </b> GeneCup answers this question by searching PubMed to find <i>sentences</i> containing gene symbols and a custom list of keywords. - These keywords are organized into a user defined ontology, which groups related keywords together for better organization of the results. + <!-- These keywords are organized into a user defined ontology, which groups related keywords together for better organization of the results. --> Human GWAS findings from <a href="https://www.ebi.ac.uk/gwas/">NHGRI-EBI GWAS catalog </a>are also included in the search. - These gene-keyword relationships are presented as an interactive graph and a table. + These gene-keyword relationships are presented as a graph or a table. <!--Gene alias often include non-specific words and are thus not included in the initial search. However, a list of alias can be found by clicking on the gene symbol in the results section. These alias then can be searched with a single click. --> - As an example, we present a curated ontology for drug addiction with over <a href="/ontology"> 300 keywords organized into seven categories.</a> - Furthermore, <b>deep learning </b> is used to distinguish automatically the sentences describing systemic stress from those describing cellular stress. - A user account (free) is needed to create custom ontologies and save the search results. + Here we present a curated ontology for drug addiction with over <a href="/ontology"> 300 keywords organized into seven categories.</a> + <b>Deep learning </b> is used to distinguish, for example, the sentences describing systemic stress from those describing cellular stress. + A user account (free) is needed to create custom ontologies and save the search results. We do not track you. </p> <p>Example: </b><a href=/progress?type=GWAS&type=addiction&type=drug&type=brain&type=stress&type=psychiatric&type=cell&type=function&query=Rgma+Penk>Rgma Penk</a>.</p> {%if ("name" not in session) %} By default, the <a href="/ontology">addiction</a> ontology is used. Custom ontologies can be created in user accounts. - Please choose keyword categories to be included in the search. <form action="/progress"> <div id="check_selection"></div> |