reference/31172892

http://rdf.ncbi.nlm.nih.gov/pubchem/reference/31172892

Outgoing Links

Predicate	Object
contentType	Journal Article
issn	1471-2105
issueIdentifier	1
pageRange	348-
publicationName	BMC Bioinformatics
startingPage	348
hasFundingAgency	http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_77e2488754b2b37f99f84e3d30d28ece http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_c5629bd1a5ca4e66edeb234d96e142e2 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_e01b2377fafe8e7c7349c9fbe5f031a9 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_20f5c1d4b573c39935d578c0bc3db503 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_6a06f795e2776f8b4caa4cc13fa47f47 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_878b407cc6ead227857ecfd4ea9f1b3d http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_7aa32fb8aafe11f6f1ecc6fe97739ed9 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_e7a58be033432d09258d295a293b5bdc http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_274de0cd095daad44a563971b32f4582 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_a286a56405ee4c5978b461efee2774ba http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_c69712507d6930bd0f8c8df12aeb228e http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_c81c82b4ad9caa060230b3c9689699b7 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_6052f262153f8377454367a4a272aa4a http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_c2de62851aee5825eefb200d2346ccd5
isSupportedBy	http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_b9475b77ed0de11f0c22d8aae54cb90e http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_9e6bc2759092521c170195f93a2ffd29 http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_41265af308783c8605f6598a2fbba26e http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_4265e1bfe5b5f646d6afa8af957dfb6f
bibliographicCitation	Zhang M, Liu Y, Zhou H, Watkins J, Zhou J. A novel nonlinear dimension reduction approach to infer population structure for low-coverage sequencing data. BMC Bioinformatics. 2021 Jun 26;22(1):348. PMID: 34174829; PMCID: PMC8236193.
creator	http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_f5bfedb4de92e5474951824ad36fe0fc http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_ff24a6f3a8e115d2cf979bed6625a097 http://rdf.ncbi.nlm.nih.gov/pubchem/author/ORCID_0000-0001-7983-0274 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_64431cad35560aa89e75eafa63def9c4 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_a9a020ae824867682fca7e743f8055a3 http://rdf.ncbi.nlm.nih.gov/pubchem/author/ORCID_0000-0003-1320-7118
date	2021-06-26-04:00^^<http://www.w3.org/2001/XMLSchema#date>
identifier	https://pubmed.ncbi.nlm.nih.gov/PMC8236193 https://pubmed.ncbi.nlm.nih.gov/34174829 https://doi.org/10.1186/s12859-021-04265-7
isPartOf	https://portal.issn.org/resource/ISSN/1471-2105 http://rdf.ncbi.nlm.nih.gov/pubchem/journal/21854
language	English
source	https://pubmed.ncbi.nlm.nih.gov/ https://www.crossref.org/ https://scigraph.springernature.com/
title	A novel nonlinear dimension reduction approach to infer population structure for low-coverage sequencing data
hasSubjectTerm	http://purl.org/au-research/vocabulary/anzsrc-for/2008/06 http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604

Total number of triples: 44.