Essential gene prediction using limited gene essentiality information–An integrative semi-supervised machine learning strategy

Sutanu Nandi; Piyali Ganguli; Ram Rup Sarkar

doi:10.1371/journal.pone.0242943

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Open Access

Peer-reviewed

Research Article

Essential gene prediction using limited gene essentiality information–An integrative semi-supervised machine learning strategy

Sutanu Nandi,

Roles Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – original draft

Affiliations Chemical Engineering and Process Development, CSIR-National Chemical Laboratory, Pune, Maharashtra, India, Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, India
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Piyali Ganguli,

Roles Formal analysis, Validation, Writing – review & editing

Affiliations Chemical Engineering and Process Development, CSIR-National Chemical Laboratory, Pune, Maharashtra, India, Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, India
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Ram Rup Sarkar

Roles Conceptualization, Supervision, Writing – review & editing

* E-mail: rr.sarkar@ncl.res.in

Affiliations Chemical Engineering and Process Development, CSIR-National Chemical Laboratory, Pune, Maharashtra, India, Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, India

https://orcid.org/0000-0001-7115-163X

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Essential gene prediction using limited gene essentiality information–An integrative semi-supervised machine learning strategy

Sutanu Nandi,
Piyali Ganguli,
Ram Rup Sarkar

Published: November 30, 2020
https://doi.org/10.1371/journal.pone.0242943

About the Authors

Sutanu Nandi

Roles Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – original draft

Affiliations Chemical Engineering and Process Development, CSIR-National Chemical Laboratory, Pune, Maharashtra, India, Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, India

Piyali Ganguli

Roles Formal analysis, Validation, Writing – review & editing

Affiliations Chemical Engineering and Process Development, CSIR-National Chemical Laboratory, Pune, Maharashtra, India, Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, India

Ram Rup Sarkar

Roles Conceptualization, Supervision, Writing – review & editing

* E-mail: rr.sarkar@ncl.res.in

Affiliations Chemical Engineering and Process Development, CSIR-National Chemical Laboratory, Pune, Maharashtra, India, Academy of Scientific & Innovative Research (AcSIR), Ghaziabad, India

https://orcid.org/0000-0001-7115-163X

Competing Interests

The authors have declared that no competing interests exist.

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Gene prediction
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Machine learning
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Machine learning algorithms
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Leishmania donovani
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Metabolic networks
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Genetic networks
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Genomics
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Support vector machines
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