MLCB2021_acceptance.xlsx

	A	B	C	D
1	ID	Status	Title	Authors
2	3	Oral	scBasset: Sequence-based modeling of single cell ATAC-seq using convolutional neural networks	Han Yuan (Calico Life Sciences)*; David R Kelley (Calico Life Sciences)
3
4
5	6	Oral	Sparse dictionary learning recovers pleiotropy from human cell fitness screens	Joshua Pan (Broad Institute)*
6
7
8	8	Oral	MAVE-NN: learning genotype-phenotype maps from multiplex assays of variant effect	Justin B Kinney (Cold Spring Harbor Laboratory)*
9
10
11	17	Oral	Towards More Realistic Simulated Datasets for Benchmarking Deep Learning Models in Regulatory Genomics	Eva I Prakash (Stanford University); Avanti Shrikumar (Stanford University)*; Anshul Kundaje (Stanford University)
12
13
14	22	Oral	Looking at the BiG picture: Incorporating bipartite graphs in drug response prediction	David Earl Hostallero (McGill University)*; Jessica Li (McGil University); Amin Emad (McGill University)
15
16
17	25	Oral	A Graph Neural Network Approach to Molecule Carcinogenicity Prediction	Philip Fradkin (Vector Institute)*; Adamo Young (University of Toronto); Lazar Atanackovic (University of Toronto); Leo J Lee (University of Toronto); Brendan Frey (U. Toronto); Bo Wang (Vector Institute)
18
19
20	33	Oral	sc-DoRI: Gene Regulatory inference from single cell multi-omics data using Interpretable Deep Learning	Manu Saraswat (German Cancer Research Center(DKFZ) and European Molecular Biology Laboratory(EMBL))*; Moritz Mall (German Cancer Research Center (DKFZ)); Oliver Stegle (German Cancer Research Center (DKFZ) & EMBL Heidelberg)
21
22
23	39	Oral	Inferring peptide coefficients from quantitative mass spectrometry data with deep learning	Ayse Dincer (Univeristy of Washington); Yang Young Lu (University of Washington); Sewoong Oh (University of Washington); William S Noble (University of Washington)*
24
25
26	40	Oral	A segmentation error aware probabilistic clustering model for highly multiplexed imaging data	Yuju Lee (University of Toronto)*; Alina Selega (Lunenfeld-Tanenbaum Research Institute); Kieran Campbell (University of Toronto)
27
28
29	41	Oral	The rate-distortion explanation identifies causal mutations driving drug resistance in bacterial whole-genome sequence data	Nick Dexter (Simon Fraser University)*; Morteza M. Saber (McGill University); B. Jesse Shapiro (McGill University); Leonid Chindelevitch (Imperial College London); Maxwell Libbrecht (Simon Fraser University)
30
31
32	43	Oral	scOrigami: Prediction of 3D chromatin structure and cis-regulatory interaction networks from single-cell chromatin accessibility data	Vianne R Gao (Weill Medical College)*
33
34
35	44	Oral	Unsupervised integration of single-cell multi-omics datasets with disproportionate cell type representation	Pinar Demetci (Brown University); Rebecca Santorella (Brown University); Bjorn Sandstede (Brown University); Ritambhara Singh (Brown University)*
36
37
38	51	Oral	Deep generative models of protein structure create new and diverse proteins	Zeming Lin (Facebook AI Reseach)*; Tom Sercu (FAIR); yann lecun (Facebook); Alex Rives (FAIR)
39
40
41	56	Oral	Towards data-driven design of context-specific regulatory elements	Peter Bromley (Altius Institute for Biomedical Sciences); Wouter Meuleman (Altius Institute for Biomedical Sciences)*
42
43
44	58	Oral	Semi-supervised single-cell cross-modality translation using Polarbear	Ran Zhang (University of Washington); William S Noble (University of Washington)*; Jean-Philippe Vert (Google)
45
46
47	64	Oral	Statistical correction of input gradients for black box models trained with categorical input features	Antonio Majdandzic (CSHL); Peter K. Koo ()*
48
49
50	4	Spotlight	Towards a Better Understanding of Reverse-Complement Equivariance for Deep Learning Models in Genomics	Hannah Zhou (Harvard University); Avanti Shrikumar (Stanford University)*; Anshul Kundaje ()
51
52
53	5	Spotlight	Multimodal Pre-Training Model for Sequence-based Prediction of Protein-Protein Interaction	Yang Xue (Baidu Inc.)*; Zijing Liu (Baidu Inc.); Xiaomin Fang (Baidu Inc.); Fan Wang (Baidu, Inc.)
54
55
56	9	Spotlight	MuDCoD: Multi-Subject Community Detection in Dynamic Gene Networks	Ali Osman Berk Şapcı (Sabancı University); Shan Lu (University of Wisconsin-Madison); Oznur Tastan (Sabanci University)*; Sunduz Keles (University of Wisconsin-Madison)
57
58
59	10	Spotlight	Simultaneous CUT&Tag profiling of the accessible and silenced regulome in single cells	Derek Janssens (Fred Hutchinson Cancer Research Center); Dominik J. Otto (Fred Hutchinson Cancer Research Center)*; Michael Meers (Fred Hutchinson Cancer Research Center); Kami Ahmad (Fred Hutchinson Cancer Research Center); Steve Henikoff (Fred Hutchinson Cancer Research Center); Manu Setty ()
60
61
62	7	Spotlight	Real-time pathogenicity prediction during genome sequencing of novel viruses and bacteria	Jakub M Bartoszewicz (Hasso Plattner Institute)*; Ulrich Genske (Hasso Plattner Institute); Bernhard Renard (Hasso Plattner Institute)
63
64
65	13	Spotlight	Compound Screening with Deep Learning for Neglected Diseases: Leishmaniasis	Jonathan A J Smith (Layer 6 AI)*; Hao Xu (Queen's University); Xinran Li (Queens University); Laurence Yang (Queens University); Jahir Gutierrez (Layer 6 AI)
66
67
68	14	Spotlight	Modeling and interpretation of label free live cell imaging accelerate morphology based in vitro chemical screens	Herve D Marie Nelly (insitro)*
69
70
71	16	Spotlight	Accelerating in-silico saturation mutagenesis using compressed sensing	Jacob Schreiber (Stanford University)*; Surag Nair (Stanford University); Akshay Balsubramani (Stanford); Anshul Kundaje (Stanford University)
72
73
74	18	Spotlight	Hi-C-LSTM: Learning representations of chromatin contacts using a recurrent neural network identifies genomic drivers of 3D genome conformation	Kevin B Dsouza (University of British Columbia)*; Max Libbrecht (Simon Fraser)
75
76
77	19	Spotlight	A novel matrix factorization model for interpreting single-cell gene expression from biologically heterogeneous data	Kun Qian (China University of Geosciences); Shiwei Fu (Rutgers, The State University of New Jersey); Hongwei Li (China University of Geosciences); Wei Vivian Li (Rutgers, The State University of New Jersey)*
78
79
80	30	Spotlight	scGraphReg: modeling gene regulations in single cells using multiomics and chromatin interactions	Alireza Karbalayghareh (Memorial Sloan Kettering Cancer Center)*; Divya Koyyalagunta (Weill Cornell Medicine ); Christina Leslie (Memorial Sloan Kettering Cancer Center)
81
82
83	32	Spotlight	Tandem Mass Spectra Prediction for Small Molecules	Adamo Young (University of Toronto)*; Hannes Rost (University of Toronto); Bo Wang (Vector Institute)
84
85
86	26	Spotlight	Contrastive Multiview Coding for Enzyme-Substrate Interaction Prediction	Apurva Kalia (Tufts University)*; Soha Hassoun (Tufts University); Dilip Krishnan (Google)
87
88
89	37	Spotlight	Linking cells across single-cell modalities by synergistic matching of neighborhood structure	Borislav Hristov (University of Washington)*; William S Noble (University of Washington); Jeff Bilmes (UW)
90
91
92	34	Spotlight	Clipper: p-value-free FDR control on high-throughput data from two conditions	Xinzhou Ge (UCLA)*; Yiling Chen (UCI); Jingyi Li (UCLA)
93
94
95	46	Spotlight	Enzyme Activity Prediction of Sequence Variants on Novel Substrates using Improved Substrate Encodings and Convolutional Pooling	Zhiqing Xu (University of Toronto, Department of Chemical Engineering and Applied Chemistry)*; Jinghao Wu ( University of Toronto, Department of Chemical Engineering and Applied Chemistry); Yun S Song (UC Berkeley); Radhakrishnan Mahadevan (University of Toronto)
96
97
98	47	Spotlight	Integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously	Ziqi Zhang (Georgia Institute of Technology)*; Xiuwei Zhang (Georgia Institute of Technology)
99
100