MLSNet: a deep learning model for predicting transcription factor binding sites
Yuchuan Zhang(Nanjing University of Science and Technology), Dong‐Jun Yu(Nanjing University of Science and Technology), Fang Ge(Nanjing University of Posts and Telecommunications), Shanshan Li(Wuxi People's Hospital), Yiwen Zhang(Harvard University), Yuming Guo(Chinese Academy of Sciences), Zhikang Wang(Australian Regenerative Medicine Institute), Xiaoyu Wang(Discovery Institute), Jiangning Song(Australian Regenerative Medicine Institute)
Cited by 16
Related Papers
<i>iFeature</i>: a Python package and web server for features extraction and selection from protein and peptide sequences
|Bioinformatics|2018|693
Emerging contaminants: A One Health perspective
|The Innovation|2024|497
Temporal Variation in Heat–Mortality Associations: A Multicountry Study
|Environmental Health Perspectives|2015|470
iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data
|Briefings in Bioinformatics|2019|436
Association analyses identify six new psoriasis susceptibility loci in the Chinese population
|Nature Genetics|2010|317