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KeySDL: sparse dictionary learning for keystone microbe identification from steady-state observations using a dynamical-systems model.

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Title: KeySDL: sparse dictionary learning for keystone microbe identification from steady-state observations using a dynamical-systems model.
Authors: Gordon M; Department of Electrical and Computer Engineering, North Carolina State University, 890 Oval Drive, Raleigh, NC, 27607, USA., Akyol TY; Department of Molecular Biology and Genetics, Aarhus University, Universitetsbyen 81, Aarhus C, 8000, Denmark., Amos B; Department of Electrical and Computer Engineering, North Carolina State University, 890 Oval Drive, Raleigh, NC, 27607, USA., Andersen SU; Department of Molecular Biology and Genetics, Aarhus University, Universitetsbyen 81, Aarhus C, 8000, Denmark., Williams C; Department of Electrical and Computer Engineering, North Carolina State University, 890 Oval Drive, Raleigh, NC, 27607, USA. cmwilli5@ncsu.edu.
Source: BioData mining [BioData Min] 2026 Feb 19; Vol. 19 (1), pp. 18. Date of Electronic Publication: 2026 Feb 19.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101319161 Publication Model: Electronic Cited Medium: Print ISSN: 1756-0381 (Print) Linking ISSN: 17560381 NLM ISO Abbreviation: BioData Min Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: KeySDL: sparse dictionary learning for keystone microbe identification from steady-state observations using a dynamical-systems model.
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  Data: <searchLink fieldCode="AU" term="%22Gordon+M%22">Gordon M</searchLink>; Department of Electrical and Computer Engineering, North Carolina State University, 890 Oval Drive, Raleigh, NC, 27607, USA.<br /><searchLink fieldCode="AU" term="%22Akyol+TY%22">Akyol TY</searchLink>; Department of Molecular Biology and Genetics, Aarhus University, Universitetsbyen 81, Aarhus C, 8000, Denmark.<br /><searchLink fieldCode="AU" term="%22Amos+B%22">Amos B</searchLink>; Department of Electrical and Computer Engineering, North Carolina State University, 890 Oval Drive, Raleigh, NC, 27607, USA.<br /><searchLink fieldCode="AU" term="%22Andersen+SU%22">Andersen SU</searchLink>; Department of Molecular Biology and Genetics, Aarhus University, Universitetsbyen 81, Aarhus C, 8000, Denmark.<br /><searchLink fieldCode="AU" term="%22Williams+C%22">Williams C</searchLink>; Department of Electrical and Computer Engineering, North Carolina State University, 890 Oval Drive, Raleigh, NC, 27607, USA. cmwilli5@ncsu.edu.
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  Data: <searchLink fieldCode="JN" term="%22101319161%22">BioData mining</searchLink> [BioData Min] 2026 Feb 19; Vol. 19 (1), pp. 18. <i>Date of Electronic Publication: </i>2026 Feb 19.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22BioMed+Central%22">BioMed Central </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101319161 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Print <i>ISSN: </i>1756-0381 (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2217560381%22">17560381 </searchLink><i>NLM ISO Abbreviation: </i>BioData Min <i>Subsets: </i>PubMed not MEDLINE
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        Value: 10.1186/s13040-026-00527-3
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      – Code: eng
        Text: English
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              Text: 2026 Feb 19
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