SIM-CE: An Advanced Simulation Platform for Studying the brain of Caenorhabditis elegans. Ramin M. Hasani, Victoria Beneder, Magdalena Fuchs, David Lung and Radu Grosu
Approximate Bayesian inference as a gauge theory. Biswa Sengupta and Karl Friston
Modeling the impact of somatic alterations in ubiquitin pathway genes across human cancers. Hatice Osmanbeyoglu and Christina Leslie
Visualizing Cancer Heterogeneity with Dynamic Flow. Teppei Nakano and Kazuki Ikeda
Predicting Cancer Heterogeneity from One-shot Biopsy. Teppei Nakano and Kazuki Ikeda
Separable Fully Connected Layers Improve Deep Learning Models for Genomics. Amr Alexandari, Avanti Shrikumar and Anshul Kundaje
Enabling rapid screening of bacterial blood infections with machine learning. Neal Jean, Chi-Sing Ho, Amr Saleh, Niaz Banaei, Jennifer Dionne and Stefano Ermon
Ask the doctor – Improving drug sensitivity predictions through active expert knowledge elicitation. Iiris Sundin, Tomi Peltola, Muntasir Mamun Majumder, Pedram Daee, Marta Soare, Homayun Afrabandpey, Caroline Heckman, Samuel Kaski and Pekka Marttinen
Contrastive Principal Component Analysis. Abubakar Abid, Vivek Bagaria, Martin Zhang and James Zou
Dealing with Stochasticity in Biological ODE Models. Hamda Ajmal, Michael Madden and Catherine Enright
Learning RNA structure (only) from structure probing data. Chuan-Sheng Foo and Cristina Pop
Inferring transcriptional regulatory programs in gynecological cancers. Hatice Osmanbeyoglu and Christina Leslie
Bacteriocin detection with distributed biological sequence representation. Md Nafiz Hamid and Iddo Friedberg
Promiscuity in gene expression of horizontally acquired DNA is driven by the contrast in promoter and recipient GC content. Antonio Gomes and Nathan Johns
Incorporating Priors and Rejection for Network Inference and Out of Sample Prediction. Jacopo Cirrone, Gloria Coruzzi, Richard Bonneau and Dennis Shasha
MERGE: Dimensionality reduction via unsupervised feature learning reveals a novel driver for sensitivity to topoisomerase II inhibitors. Su-In Lee, Safiye Celik, Benjamin A. Logsdon, Scott M. Lundberg, Timothy J. Martins, Vivian M. Oehler, Elihu H. Estey, Chris P. Miller, Sylvia Chien, Akanksha Saxena, C. Anthony Blau and Pamela Becker
Dilated Convolutions for Modeling Long-Distance Genomic Dependencies. Ankit Gupta and Alexander Rush
Bayesian Network Learning for Molecular Marker Discovery in Alzheimer’s Disease and Resilience. Safiye Celik, Shubhabrata Mukherjee, C. Dirk Keene, Paul K. Crane and Su-In Lee
Prioritizing Small Molecules as Candidates for Drug Repositioning using Machine Learning. Shameer Khader, Kipp W. Johnson, Benjamin S. Glicksberg, Rachel Hodos, Ben Readhead, Max S. Tomlinson and Joel Dudley
Drug molecular activity prediction via sparsity grouped multitask learning. Meghana Kshirsagar, Eunho Yang and Aurelie Lozano
A Novel Computational Approach for Global Alignment for Multiple Biological Networks. Engelbert Mephu Nguifo, Waritheddine Djeddi and Sadok Ben Yahia
DeepATAC: A deep-learning method to estimate regulatory factor binding activity from ATAC-seq signals. Naozumi Hiranuma, Scott Lundberg and Su-In Lee
The Bottlenecks in Biological Networks. Hamidreza Mahyar, Elahe Ghalebi K., Hamid R. Rabiee and Radu Grosu
Uncovering the gene usage of human tissue cells with joint factorized embeddings. Assya Trofimov, Joseph Paul Cohen, Claude Perreault, Yoshua Bengio and Sebastien Lemieux