Predicting Transcription Factor Binding Using Ensemble Random Forest Models

Behjati Ardakani, Fatemeh; Schmidt, Florian; Schulz, Marcel Holger

doi:10.12688/f1000research.16200.2

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Predicting Transcription Factor Binding Using Ensemble Random Forest Models

Behjati Ardakani, F., Schmidt, F., & Schulz, M. H. (2019). Predicting Transcription Factor Binding Using Ensemble Random Forest Models. Faculty of 1000 Research, 7: 1603. doi:10.12688/f1000research.16200.2.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0005-69DC-E Version Permalink: https://hdl.handle.net/21.11116/0000-0005-69DD-D

Genre: Journal Article

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Creators:
Behjati Ardakani, Fatemeh¹, Author
Schmidt, Florian¹, Author
Schulz, Marcel Holger¹, Author

Affiliations:
1Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society, ou_40046

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Language(s): eng - English

Dates: Published Online: 2019

Publication Status: Published online

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Identifiers: DOI: 10.12688/f1000research.16200.2
BibTex Citekey: Behjati2019

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Title: Faculty of 1000 Research

Abbreviation : F1000Research

Source Genre: Journal

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Publ. Info: London : BioMed Central

Pages: 30 p. Volume / Issue: 7 Sequence Number: 1603 Start / End Page: - Identifier: ISSN: 2046-1402
CoNE: https://pure.mpg.de/cone/journals/resource/2046-1402