457 citations · 473 across the 8 of their papers we have counts for
8 papers
Insights into performance evaluation of com-pound-protein interaction prediction methods
Adiba Yaseen, Imran Amin, Naeem Akhter +2
Motivation: Machine learning based prediction of compound-protein interactions (CPIs) is important for drug design, screening and repurposing studies and can improve the efficiency…
Comprehensive Evaluation of Deep Learning Architectures for Prediction of DNA/RNA Sequence Binding Specificities
Ameni Trabelsi, Mohamed Chaabane, Asa Ben Hur
Motivation: Deep learning architectures have recently demonstrated their power in predicting DNA- and RNA-binding specificities. Existing methods fall into three classes: Some are…
Ten ways to fool the masses with machine learning
Fayyaz Minhas, Amina Asif, Asa Ben-Hur
If you want to tell people the truth, make them laugh, otherwise they'll kill you. (source unclear) Machine learning and deep learning are the technologies of the day for developin…
pyLEMMINGS: Large Margin Multiple Instance Classification and Ranking for Bioinformatics Applications
Amina Asif, Wajid Arshad Abbasi, Farzeen Munir +2
Motivation: A major challenge in the development of machine learning based methods in computational biology is that data may not be accurately labeled due to the time and resources…
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
Yuxiang Jiang, Tal Ronnen Oron, Wyatt T Clark +144
Background: The increasing volume and variety of genotypic and phenotypic data is a major defining characteristic of modern biomedical sciences. At the same time, the limitations i…
On probabilistic analog automata
A. Ben-Hur, A. Roitershtein, H. Siegelmann
We consider probabilistic automata on a general state space and study their computational power. The model is based on the concept of language recognition by probabilistic automata…