Searching across hundreds of databases
Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
URL: https://github.com/lkmklsmn/DrivAER
Proper Citation: DrivAER (RRID:SCR_019076)
Description: Software tool as method for identification of driving transcriptional programs based on AutoEncoder derived Relevance scores. Infers relevance scores for transcriptional programs with respect to specified outcomes of interest in single-cell RNA sequencing data, such as psuedotemporal ordering or disease status.Used for manifold interpretation in scRNA-seq data.
Synonyms: Driving transcriptional programs using AutoEncoder based Relevance scores
Resource Type: data analysis software, data processing software, software resource, software application
Keywords: Manifold interpretation, scRNAseq data, relevance scores infering, transcriptional program, psuedotemporal ordering, disease status, data, bio.tools
Expand AllWe found {{ ctrl2.mentions.total_count }} mentions in open access literature.
We have not found any literature mentions for this resource.
We are searching literature mentions for this resource.
Most recent articles:
{{ mention._source.dc.creators[0].familyName }} {{ mention._source.dc.creators[0].initials }}, et al. ({{ mention._source.dc.publicationYear }}) {{ mention._source.dc.title }} {{ mention._source.dc.publishers[0].name }}, {{ mention._source.dc.publishers[0].volume }}({{ mention._source.dc.publishers[0].issue }}), {{ mention._source.dc.publishers[0].pagination }}. (PMID:{{ mention._id.replace('PMID:', '') }})
Check
for all resource mentions.
A list of researchers who have used the resource and an author search tool
A list of researchers who have used the resource and an author search tool. This is available for resources that have literature mentions.
No rating or validation information has been found for DrivAER.
No alerts have been found for DrivAER.
Source: SciCrunch Registry
Welcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
