Work

Data Sets and Results for "Improved data sets and evaluation methods for the automatic prediction of DNA-binding proteins"

Year: 2021

Type: dataset

Abstract: Data set and results for "Improved data sets and evaluation methods for the automatic prediction of DNA-binding proteins" The file "dna_binding_protein_sequences.zip" has the testing and training sets from the paper: RLL - "random_<train/test>_full_1000.csv" RSL - "random_<train/test>_50.csv" RS&LL - "random_<train/test>_50_1000.csv" RLL where included positive examples have verified DNA binding activity - "random_<train/test>_hq_1000.csv" The results files are named similarly. The species data sets are derived from "uniprot_data_bac.tab" and "uniprot_data_not_bac.tab." See code. The ESM embeddings used by the XGBoost model are in "dna_binding_protein_esm.zip"

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.5137961

Authors: Zaitzeff, Alexander, Leiby, Nick, Motta, Francis, Haase, Steven, Singer, Jedediah

Institutions: Florida Atlantic University, Duke University

Language: English

Topic: Machine Learning in Bioinformatics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

OpenAlex ID: W4393834100

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