Publications

Open Biomedical Network Benchmark A Python Toolkit for Benchmarking Datasets with Biomedical Networks

Submitted to MLCB’23
Renming Liu, Arjun Krishnan
Paper / Software / Benchmark

CONE: COntext-specific Network Embedding via Contextualized Graph Attention

Submitted to LoG’23
Renming Liu^*, Hao Yuan^*, Kayla A Johnson, Arjun Krishnan
Paper / GitHub

A General Single-Cell Analysis Framework via Conditional Diffusion Generative Models

Submitted to ICLR’24
Wenzhuo Tang^*, Renming Liu^*, Hongzhi Wen, Xinnan Dai, Jiayuan Ding, Hang Li, Wenqi Fan, Yuying Xie, Jiliang Tang
Paper / GitHub

Graph Positional and Structural Encoder

Submitted to ICLR’24
Renming Liu^*, Semih Cantürk^*, Olivier Lapointe-Gagné, Vincent Létourneau, Guy Wolf, Dominique Beaini, Ladislav Rampášek
Paper / GitHub

Joint representation of molecular networks from multiple species improves gene classification

Submitted to PLOS Computational Biology
Christopher A Mancuso, Kayla A Johnson, Renming Liu, Arjun Krishnan
Paper / GitHub

SpatialCTD: a large-scale TME spatial transcriptomic dataset to evaluate cell type deconvolution for immuno-oncology

Submitted to RECOMB’24
Jiayuan Ding, Julian Venegas, Qiaolin Lu, Yixin Wang, Lidan Wu, Wei Jin, Hongzhi Wen, Renming Liu, Wenzhuo Tang, Zhaoheng Li, Wangyang Zuo, Yi Chang, Yu Leo Lei, View ORCID ProfilePatrick Danaher, Yuying Xie, Jiliang Tang
Paper

Single Cells Are Spatial Tokens: Transformers for Spatial Transcriptomic Data Imputation

Submitted to RECOMB’24
Hongzhi Wen, Wenzhuo Tang, Wei Jin, Jiayuan Ding, Renming Liu, Feng Shi, Yuying Xie, Jiliang Tang
Paper

Deep Learning in Single-Cell Analysis

Submitted to ACM Transactions on Intelligent Systems and Technology
Dylan Molho^*, Jiayuan Ding^*, Zhaoheng Li, Hongzhi Wen, Wenzhuo Tang, Yixin Wang, Julian Venegas, Wei Jin, Renming Liu, Runze Su, Patrick Danaher, Robert Yang, Yu Leo Lei, Yuying Xie, Jiliang Tang
Paper

DANCE: A Deep Learning Library and Benchmark Platform for Single-Cell Analysis

Submitted to Genome Biology
Jiayuan Ding^*, Hongzhi Wen^*, Wenzhuo Tang^*, Renming Liu^*, Zhaoheng Li, Julian Venegas, Runze Su, Dylan Molho, Wei Jin, Wangyang Zuo, Yixin Wang, Robert Yang, Yuying Xie, Jiliang Tang
Paper / GitHub / PyPI

Single-Cell Multimodal Prediction via Transformers

Published in CIKM'23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Wenzhuo Tang^*, Hongzhi Wen^*, Renming Liu^*, Jiayuan Ding, Wei Jin, Yuying Xie, Hui Liu, Jiliang Tang
Paper / GitHub

PyGenePlexus: a Python package for gene discovery using network-based machine learning

Published in Bioinformatics, 2023

Christopher A Mancuso^*, Renming Liu^*, Arjun Krishnan
Paper / GitHub / PyPI

Accurately modeling biased random walks on weighted networks using node2vec+

Published in Bioinformatics, 2023

Renming Liu, Matthew Hirn, Arjun Krishnan
Paper / Software / Benchmark

Taxonomy of Benchmarks in Graph Representation Learning

Published in LoG'22: Learning on Graphs Conference, 2022

Renming Liu^*, Semih Cantürk^*, Frederik Wenkel, Sarah McGuire, Xinyi Wang, Anna Little, Leslie O’Bray, Michael Perlmutter, Bastian Rieck, Matthew Hirn, Guy Wolf, Ladislav Rampášek
Paper / GitHub

Applications of an Association Activity Coefficient Model, NRTL-PA, to Alcohol-Containing Mixtures

Published in Industrial & Engineering Chemistry Research, 2022

Aseel M Bala, Renming Liu, Lars Peereboom, Carl T Lira
Paper

GenePlexus: a web-server for gene discovery using network-based machine learning

Published in Nucleic Acids Research, 2022

Christopher A Mancuso, Patrick S Bills, Douglas Krum, Jacob Newsted, Renming Liu, Arjun Krishnan
Paper / GitHub / WebServer

PecanPy: a fast, efficient and parallelized Python implementation of node2vec

Published in Bioinformatics, 2021

Renming Liu, Arjun Krishnan
Paper / GitHub

Supervised learning is an accurate method for network-based gene classification

Published in Bioinformatics, 2020

Renming Liu^*, Christopher A Mancuso^*, Anna Yannakopoulos, Kayla A Johnson, Arjun Krishnan
Paper / GitHub