Accepted Abstracts

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