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Evaluating sequence-to-function deep learning models for ancestry-stratified regulatory variant effect prediction using multi-ancestry blood eQTLs.

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Title: Evaluating sequence-to-function deep learning models for ancestry-stratified regulatory variant effect prediction using multi-ancestry blood eQTLs.
Authors: Sun X, Mews M, Wheeler NR, Benchek P, Gu T, Gomez L, Mustafa Y, Wang LS, Leung YY, Schellenberg GD, Pericak-Vance MA, Haines JL, Griswold AJ, Bush WS
Source: BioRxiv : the preprint server for biology [bioRxiv] 2026 Jun 26. Date of Electronic Publication: 2026 Jun 26.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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DbLabel: MEDLINE Ultimate
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PubType: Academic Journal
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  Data: Evaluating sequence-to-function deep learning models for ancestry-stratified regulatory variant effect prediction using multi-ancestry blood eQTLs.
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  Data: <searchLink fieldCode="AU" term="%22Sun+X%22">Sun X</searchLink><br /><searchLink fieldCode="AU" term="%22Mews+M%22">Mews M</searchLink><br /><searchLink fieldCode="AU" term="%22Wheeler+NR%22">Wheeler NR</searchLink><br /><searchLink fieldCode="AU" term="%22Benchek+P%22">Benchek P</searchLink><br /><searchLink fieldCode="AU" term="%22Gu+T%22">Gu T</searchLink><br /><searchLink fieldCode="AU" term="%22Gomez+L%22">Gomez L</searchLink><br /><searchLink fieldCode="AU" term="%22Mustafa+Y%22">Mustafa Y</searchLink><br /><searchLink fieldCode="AU" term="%22Wang+LS%22">Wang LS</searchLink><br /><searchLink fieldCode="AU" term="%22Leung+YY%22">Leung YY</searchLink><br /><searchLink fieldCode="AU" term="%22Schellenberg+GD%22">Schellenberg GD</searchLink><br /><searchLink fieldCode="AU" term="%22Pericak-Vance+MA%22">Pericak-Vance MA</searchLink><br /><searchLink fieldCode="AU" term="%22Haines+JL%22">Haines JL</searchLink><br /><searchLink fieldCode="AU" term="%22Griswold+AJ%22">Griswold AJ</searchLink><br /><searchLink fieldCode="AU" term="%22Bush+WS%22">Bush WS</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22101680187%22">BioRxiv : the preprint server for biology</searchLink> [bioRxiv] 2026 Jun 26. <i>Date of Electronic Publication: </i>2026 Jun 26.
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  Data: <i>Country of Publication: </i>United States <i>NLM ID: </i>101680187 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2692-8205 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2226928205%22">26928205 </searchLink><i>NLM ISO Abbreviation: </i>bioRxiv <i>Subsets: </i>PubMed not MEDLINE
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      – Type: doi
        Value: 10.64898/2026.06.22.730889
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      – Code: eng
        Text: English
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      – TitleFull: Evaluating sequence-to-function deep learning models for ancestry-stratified regulatory variant effect prediction using multi-ancestry blood eQTLs.
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            – D: 26
              M: 06
              Text: 2026 Jun 26
              Type: published
              Y: 2026
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