Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2023
Accurate prediction of TCR binding affinity to a target antigen is important for development of immunotherapy strategies. Recent computational methods were built on various deep neural networks and used the evolutionary-based distance matrix BLOSUM t...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2023
Several biomedical applications contain multiple treatments from which we want to estimate the causal effect on a given outcome. Most existing Causal Inference methods, however, focus on single treatments. In this work, we propose a neural network th...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2023
Identifying effective target-disease associations (TDAs) can alleviate the tremendous cost incurred by clinical failures of drug development. Although many machine learning models have been proposed to predict potential novel TDAs rapidly, their cred...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2023
Although protein sequence data is growing at an ever-increasing rate, the protein universe is still sparsely annotated with functional and structural annotations. Computational approaches have become efficient solutions to infer annotations for unlab...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2023
The visual classification of cell images according to differences in the spatial patterns of subcellular structure is an important methodology in cell and developmental biology. Experimental perturbation of cell function can induce changes in the spa...
Bioinformatics (Oxford, England)
Jan 1, 2023
MOTIVATION: Over 300 000 protein-protein interaction (PPI) pairs have been identified in the human proteome and targeting these is fast becoming the next frontier in drug design. Predicting PPI sites, however, is a challenging task that traditionally...
Bioinformatics (Oxford, England)
Jan 1, 2023
MOTIVATION: We present dnadna, a flexible python-based software for deep learning inference in population genetics. It is task-agnostic and aims at facilitating the development, reproducibility, dissemination and re-usability of neural networks desig...
Bioinformatics (Oxford, England)
Jan 1, 2023
MOTIVATION: Gaining structural insights into the protein-protein interactome is essential to understand biological phenomena and extract knowledge for rational drug design or protein engineering. We have previously developed DeepRank, a deep-learning...
Bioinformatics (Oxford, England)
Jan 1, 2023
MOTIVATION: Compound-protein interaction (CPI) plays an essential role in drug discovery and is performed via expensive molecular docking simulations. Many artificial intelligence-based approaches have been proposed in this regard. Recently, two type...
Bioinformatics (Oxford, England)
Jan 1, 2023
MOTIVATION: While multi-channel fluorescence microscopy is a vital imaging method in biological studies, the number of channels that can be imaged simultaneously is limited by technical and hardware limitations such as emission spectra cross-talk. On...