What Are We Depressed About When We Talk About COVID-19: Mental Health Analysis on Tweets Using Natural Language Processing. - Irene Li; Yixin Li; Tianxiao Li 001; Sergio Álvarez-Napagao; Dario Garcia-Gasulla; Toyotaro Suzumura (SGAI Conf., 2020)

TopicNet: a framework for measuring transcriptional regulatory network change. - Shaoke Lou; Tianxiao Li 001; Xiangmeng Kong; Jing Zhang 062; Jason Liu 003; Donghoon Lee 006; Mark Gerstein (Bioinform., 2020)

Latent-space embedding of expression data identifies gene signatures from sputum samples of asthmatic patients. - Shaoke Lou; Tianxiao Li 001; Daniel Spakowicz; Xiting Yan; Geoffrey Lowell Chupp; Mark Gerstein (BMC Bioinform., 2020)

What are We Depressed about When We Talk about COVID19: Mental Health Analysis on Tweets Using Natural Language Processing. - Irene Li; Yixin Li; Tianxiao Li 001; Sergio Álvarez-Napagao; Darío García (CoRR, 2020)

Global Data Science Project for COVID-19 Summary Report. - Dario Garcia-Gasulla; Sergio Álvarez-Napagao; Irene Li; Hiroshi Maruyama; Hiroki Kanezashi; Raquel Pérez-Arnal; Kunihiko Miyoshi; Euma Ishii; Keita Suzuki; Sayaka Shiba; Mariko Kurokawa; Yuta Kanzawa; et al. (CoRR, 2020)

Unsupervised Cross-Domain Prerequisite Chain Learning using Variational Graph Autoencoders. - Irene Li; Vanessa Yan; Tianxiao Li 001; Rihao Qu; Dragomir R. Radev (ACL/IJCNLP (2), 2021)

Gene Tracer: a smart, interactive, voice-controlled Alexa skill For gene information retrieval and browsing, mutation annotation and network visualization. - Shaoke Lou; Tianxiao Li 001; Jason Liu 003; Mark Gerstein (Bioinform., 2021)

Heterogeneous Graph Neural Networks for Multi-label Text Classification. - Irene Li; Tianxiao Li 001; Yixin Li; Ruihai Dong; Toyotaro Suzumura (CoRR, 2021)

Disentangled Wasserstein Autoencoder for T-Cell Receptor Engineering. - Tianxiao Li 001; Hongyu Guo; Filippo Grazioli; Mark Gerstein; Martin Renqiang Min (NeurIPS, 2023)

Constructing a full, multiple-layer interactome for SARS-CoV-2 in the context of lung disease: Linking the virus with human genes and microbes. - Shaoke Lou; Mingjun Yang; Tianxiao Li 001; Weihao Zhao; Hannah Cevasco; Yucheng T. Yang; Mark Gerstein (PLoS Comput. Biol., 2023)

A survey of generative AI for de novo drug design: new frontiers in molecule and protein generation. - Xiangru Tang; Howard Dai; Elizabeth Knight; Fang Wu; Yunyang Li; Tianxiao Li 001; Mark Gerstein (Briefings Bioinform., 2024)

A Survey of Generative AI for De Novo Drug Design: New Frontiers in Molecule and Protein Generation. - Xiangru Tang; Howard Dai; Elizabeth Knight; Fang Wu; Yunyang Li; Tianxiao Li 001; Mark Gerstein (CoRR, 2024)

Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation. - Haoran Liu; Youzhi Luo; Tianxiao Li 001; James Caverlee; Martin Renqiang Min (AAAI, 2025)

Exploring the Role of Knowledge Graph-Based RAG in Japanese Medical Question Answering with Small-Scale LLMs. - Yingjian Chen; Feiyang Li; Xingyu Song; Tianxiao Li 001; Zixin Xu; Xiujie Chen; Issey Sukeda; Irene Li (SLM4Health@AIME, 2025)

MKG-Rank: Enhancing Large Language Models with Knowledge Graph for Multilingual Medical Question Answering. - Feiyang Li; Yingjian Chen; Haoran Liu; Rui Yang 016; Han Yuan; Yuang Jiang; Tianxiao Li 001; Edison Marrese-Taylor; Hossein Rouhizadeh; Yusuke Iwasawa; Douglas Teodoro; Yutaka Matsuo; et al. (CoRR, 2025)