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: http://nagasakilab.csml.org/hla/
Proper Citation: HLA-VBSeq (RRID:SCR_022284)
Description: Software for accurate HLA typing at full resolution from whole genome sequencing data. Used to estimate the most likely HLA types from high throughput sequencing data.
Resource Type: data analysis software, software application, software resource, data processing software
Defining Citation: PMID:25708870
Keywords: HLA types estimation, sequencing data, whole genome sequencing data, high throughput sequencing data
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 HLA-VBSeq.
No alerts have been found for HLA-VBSeq.
Source: SciCrunch Registry
The NIDDK Information Network (dkNET) serves the needs of basic and clinical investigators by providing seamless access to large pools of data and research resources relevant to the mission of The National Institute of Diabetes Digestive and Kidney Diseases (NIDDK). dkNET is hosted at University of California San Diego, and is supported by NIH NIDDK grant 2U24DK097771-09.
Email: info_at_ dknet.org
