Preprints/Submitted

• Sayali Alatkar, Daifeng Wang, CMOT: Cross Modality Optimal Transport for multimodal inference, in revision, Biorxiv
• Noah Cohen Kalafut, Xiang Huang, Daifeng Wang, JAMIE: Joint Variational Autoencoders for Multi-Modal Imputation and Embedding, in revision, Biorxiv
• Pramod Bharadwaj Chandrashekar, Jiebiao Wang, Gabriel E. Hoffman, Chenfeng He, Ting Jin, Sayali Alatkar, Saniya Khullar, Jaroslav Bendl, John F. Fullard, Panagiotis Roussos, Daifeng Wang, DeepGAMI: Deep biologically guided auxiliary learning for multimodal integration and imputation to improve phenotype prediction, in revision, Biorxiv

Papers

(Bold: lab members; *co-first-author, equal contribution; # co-corresponding author)

2023

• Chenfeng He, Noah Cohen Kalafut, Soraya O. Sandoval, Ryan Risgaard, Carissa L. Sirois, Chen Yang, Saniya Khullar, Marin Suzuki, Xiang Huang, Qiang Chang, Xinyu Zhao, Andre M.M. Sousa, Daifeng Wang, BOMA – a machine learning framework for comparative gene expression analysis across brains and organoids, Cell Reports Methods, 3, 100409, 2023
• Saniya Khullar, Daifeng Wang, Predicting brain-regional gene regulatory networks from multi-omics for Alzheimer’s disease phenotypes and Covid-19 severity, Human Molecular Genetics, ddad009, 2023
• Daifeng Wang, John R. Pruett Jr., Computational approaches to address data challenges in intellectual and developmental disabilities research, Journal of Neurodevelopmental Disorders, 15, 2, 2023 (Editorial for IDDRC special issue 2022)

2022

• Shuang Liu*, Hyejung Won*, Declan Clarke*, Nana Matoba, Saniya Khullar, Yudi Mu, Daifeng Wang^#, Mark Gerstein^#, Illuminating links between cis-regulators and trans-acting variants in the human prefrontal cortex, Genome Medicine, 14, 133, 2022
• Michael J. Gandal, Jillian R. Haney, Brie Wamsley, Chloe X. Yap, Sepideh Parhami, Prashant S. Emani, Nathan Chang, George T. Chen, Gil D. Hoftman, Diego de Alba, Gokul Ramaswami, Christopher L. Hartl, Arjun Bhattacharya, Chongyuan Luo, Ting Jin, Daifeng Wang, Riki Kawaguchi, Diana Quintero, Jing Ou, Ye Emily Wu, Neelroop N. Parikshak, Vivek Swarup, T. Grant Belgard, Mark Gerstein, Bogdan Pasaniuc, Daniel H. Geschwind, Broad transcriptomic dysregulation across the cerebral cortex in ASD, Nature, 611, 532–539, 2022
• Chirag Gupta, Jielin Xu, Ting Jin, Saniya Khullar, Xiaoyu Liu, Sayali Alatkar, Feixiong Cheng, Daifeng Wang, Single-cell network biology characterizes cell-type gene regulation for drug repurposing and phenotype prediction in Alzheimer’s disease, PLoS Computational Biology, 18(7): e1010287, 2022
• Sahar Javadi, Yue Li, Jie Sheng, Lucy Zhao, Yao Fu, Daifeng Wang, Xinyu Zhao, Sustained correction of hippocampal neurogenic and cognitive deficits after a brief treatment by Nutlin-3 in a mouse model of Fragile X Syndrome, BMC Medicine, 20, 163, 2022
• Yathindar Giffin-Rao, Jie Sheng, Bennett Strand, Ke Xu, Leslie Huang, Margaret Medo, Kirstin A. Risgaard, Samuel Dantinne, Sruti Mohan, Aratrika Keshan, Roger A. Daley. Jr., Bradley Levesque, Lindsey Amundson, Rebecca Reese, André M.M. Sousa, Yunlong Tao, Daifeng Wang, Su-Chun Zhang, Anita Bhattacharyya, Altered patterning of trisomy 21 interneuron progenitors, Stem Cell Reports, 17, 1-4, 2022
• Chirag Gupta, Pramod Chandrashekar, Chenfeng He, Ting Jin, Saniya Khullar, Qiang Chang, Daifeng Wang, Bringing machine learning to research on intellectual and developmental disabilities: taking inspiration from neurological diseases, Journal of Neurodevelopmental Disorders, 14, 28, 2022 (IDDRC 2022 special issue on computational neuroscience)
• Nam D Nguyen, Jiawei Huang, Daifeng Wang, A deep manifold-regularized learning model for improving phenotype prediction from multi-modal data, Nature Computational Science, 2, 38–46, 2022 (News & Views)
• Cui-Xiang Lin, Hong-Dong Li, Chao Deng, Weisheng Liu, Shannon Erhardt, Fang-Xiang Wu, Xing-Ming Zhao, Yuanfang Guan, Jun Wang, Daifeng Wang, Bin Hu, Jianxin Wang, An integrated brain-specific network identifies genes associated with neuropathologic and clinical traits of Alzheimer’s disease, Briefings in Bioinformatics, 23(1):bbab522, 2022

2021

• Ali Fathi, Sakthikumar Mathivanan, Linghai Kong, Andrew J Petersen, Cole R. K. Harder, Jasper Block, Julia Marie Miller, Anita Bhattacharyya, Daifeng Wang, Su-Chun Zhang, Chemically induced senescence in human stem cell-derived neurons promotes phenotypic presentation of neurodegeneration, Aging Cell, e13541, 2021
• Jiawei Huang, Jie Sheng, Daifeng Wang, Manifold learning analysis suggests strategies for aligning single-cell multi-modalities and revealing functional genomics for neuronal electrophysiology, Communications Biology, 4, 1308, 2021
• Ting Jin*, Peter Rehani*, Mufang Ying*, Jiawei Huang, Shuang Liu, Panos Roussos, Daifeng Wang, scGRNom: a computational pipeline of integrative multi-omics analyses for predicting cell-type disease genes and regulatory networks, Genome Medicine, 13, 95, 2021
• Minjie Shen, Yu Guo, Qiping Dong, Yu Gao, Michael E. Stockton, Meng Li, Sudharsan Kannan, Tomer Korabelnikov, Keegan A. Schoeller, Carissa L. Sirois, Chen Zhou, Jonathan Le, Daifeng Wang, Qiang Chang, Qian-Quan Sun, Xinyu Zhao, FXR1 regulation of parvalbumin interneurons in the prefrontal cortex is critical for schizophrenia-like behaviors, Molecular Psychiatry, 2021
• Nam D Nguyen, Ting Jin, Daifeng Wang, Varmole: A biologically drop-connect deep neural network model for prioritizing disease risk variants and genes, Bioinformatics, 37 (12), 1772-1775, 2021
• Ting Jin*, Nam D Nguyen*, Flaminia Talos, Daifeng Wang, ECMarker: Interpretable machine learning model identifies gene expression biomarkers predicting clinical outcomes and reveals molecular mechanisms of human disease in early stages, Bioinformatics, 37 (8), 1115-1124, 2021
• Kunling Huang, Yuchang Wu, Junha Shin, Ye Zheng, Alireza Fotuhi Siahpirani, Yupei Lin, Zheng Ni, Jiawen Chen, Jing You, Sunduz Keles, Daifeng Wang, Sushmita Roy, Qiongshi Lu, Transcriptome-wide transmission disequilibrium analysis identifies novel risk genes for autism spectrum disorder, PLoS Genetics, 17(2): e1009309, 2021

2020

• Yu Gao, Minjie Shen, Jose Carlos Gonzalez, Qiping Dong, Sudharsan Kannan, Johnson T Hoang, Brian E Eisinger, Jyotsna Pandey, Sahar Javadi, Qiang Chang, Daifeng Wang, Linda Overstreet-Wadiche, Xinyu Zhao, RGS6 Mediates Effects of Voluntary Running on Adult Hippocampal Neurogenesis, Cell Reports, 32(5):107997, 2020
• Koon-Kiu Yan*, Daifeng Wang*, Kun Xiong, Mark Gerstein, Comparing technological development and biological evolution from a network perspective, Cell Systems 10 (3), P219-222, 2020
• Jing Zhang, Donghoon Lee, … , Kevin P. White, Mark Gerstein including Daifeng Wang, An integrative ENCODE resource for cancer genomics, Nature Communications, 11, 3696, 2020
• Nam D Nguyen, Daifeng Wang, Multi-view learning for understanding functional multiomics, PLoS Computational Biology, 16(4): e1007677, 2020

2019

• Nam D Nguyen, Ian K Blaby, Daifeng Wang, ManiNetCluster: A Manifold Learning Approach to Reveal the Functional Linkages Across Multiple Gene Networks, BMC Genomics 20, 1003, 2019
• John A Haley, Christian F Ruiz, Emily D Montal, Daifeng Wang, John D Haley, Geoffrey D Girnun, Decoupling of Nrf2 Expression Promotes Mesenchymal State Maintenance in Non-Small Cell Lung Cancer, Cancers,  2019, 11(10), 1488
• Mohamed F Salama, Mengling Liu, Christopher J Clarke, Mel Pilar Espaillat, John D Haley, Ting Jin, Daifeng Wang, Lina M Obeid, Yusuf A Hannun, PKCα is required for Akt-mTORC1 activation in non-small cell lung carcinoma (NSCLC) with EGFR mutation, Oncogene, 38, 7311–7328, 2019

2018

• Daifeng Wang*, Shuang Liu*, …, PsychENCODE Consortium, Nenad Sestan, Andrew E. Jaffe, Kevin White, Zhiping Weng, Daniel H. Geschwind, James Knowles, Mark Gerstein, Comprehensive functional genomic resource and integrative model for the human brain, Science, 362, 1266, 2018 (New York Times)
• Michael J Gandal, Pan Zhang, …, Daifeng Wang, …, PsychENCODE Consortium, …, Daniel H. Geschwind, Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder, Science, 362, 1265, 2018
• Mingfeng Li*, Gabriel Santpere*, …, Daifeng Wang, …, BrainSpan Consortium, PsychENCODE Consortium: Developmental Subgroup, …, Nenad Sestan, Integrative Functional Genomic Analysis of Human Brain Development and Neuropsychiatric Risk, Science, 362, 1264, 2018
• PsychENCODE consortium including Daifeng Wang, Revealing the brain’s molecular architecture, Science, 2018 Dec 14;362(6420):1262-1263
• Adam P Arkin, Robert W Cottingham, Christopher S Henry, Nomi L Harris, Rick L Stevens, Sergei Maslov, Paramvir Dehal, Doreen Ware, …, Daifeng Wang, Fangfang Xia, Hyunseung Yoo, Shinjae Yoo, Dantong Yu, KBase: The United States Department of Energy Systems Biology Knowledgebase, Nature Biotechnology, 36(7):566-569, 2018
• Pedro Alves, Shuang Liu, Daifeng Wang^# and Mark Gerstein^#, Multiple-Swarm Ensembles: Improving the Predictive Power and Robustness of Predictive Models and Its Use in Computational Biology, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15(3):926-933, 2018
• Zongdong Li, Natasha M. Nesbitt, Lisa E.Malone, Dimitri V. Gnatenko, Song Wu, Daifeng Wang, Wei Zhu, Geoffrey D. Girnun, Wadie F. Bahou, Heme degradation enzyme biliverdin IXB reductase is required for stem cell glutamine metabolism, Biochemical Journal, 475(6):1211-1223, 2018

2017

• Daifeng Wang^#, John D. Haley and Patricia Thompson^#, Comparative gene co-expression network analysis of epithelial to mesenchymal transition reveals lung cancer progression stages, BMC Cancer, 17:830, 2017

2016

• Daifeng Wang, Fei He, Sergei Maslov, Mark Gerstein, DREISS: Using state-space models to infer the dynamics of gene expression driven by external and internal regulatory networks, PLoS Computational Biology, 12(10): e1005146, 2016
• Daifeng Wang, Koon-Kiu Yan, Joel Rozowsky, Eric Pan, Mark Gerstein, Temporal dynamics of collaborative networks driven by large scientific consortia, Trends in Genetics, 32, 251-253, 2016
• Koon-Kiu Yan*, Daifeng Wang*, Anurag Sethi, Robert Kitchen, Paul Muir, Chao Cheng, Mark Gerstein, Matchmaking hairballs – insights from cross-disciplinary network comparison, Cell Systems, 2, 147-157, 2016 (featured front-matter)
• Paul Muir, Shantao Li, Shaoke Lou, Daifeng Wang, Daniel Spakowicz, Leonidas Salichos, Jing Zhang, Farren Isaacs, George M. Weinstock, Joel Rozowsky, Mark Gerstein, The real cost of sequencing: scaling computation to keep pace with data generation, Genome Biology, 17:53, 2016
• Fei He, Shinjae Yoo, Daifeng Wang, Sunita Kumari, Mark Gerstein, Doreen Ware, Sergei Maslov, Large-scale atlas of microarray data reveals biological landscape of gene expression in Arabidopsis, The Plant Journal, 86(6), 472-480, 2016

Before 2016

• The PsychENCODE Consortium including Daifeng Wang, The PsychENCODE Project Consortium, Nature Neuroscience, 18, 1707-1712, 2015
• Daifeng Wang, Koon-Kiu Yan, Cristina Sisu, Chao Cheng, Joel Rozowsky, William Meyerson, Mark Gerstein, Loregic: A method to characterize the cooperative logic of regulatory factors, PLoS Computational Biology 11(4): e1004132, 2015 (featured article)
• Chao Cheng, Erik Andrews, Koon-Kiu Yan, Matthew Ung, Daifeng Wang, Mark Gerstein, An Approach for Determining and Measuring Network Hierarchy: Application to Comparing the Phosphorylome and the Regulome, Genome Biology, 16:63, 2015
• Shuang Liu, Anjali Datta, Derek Ho, Jordan Dwelle, Daifeng Wang, Thomas E. Milner, H. Grady Rylander III, Mia K. Markey, Effect of image registration on longitudinal analysis of retinal nerve fiber layer thickness of non-human primates using Optical Coherence Tomography (OCT), BMC Eye and Vision, 2:3, 2015
• Mark Gerstein*, Joel Rozowsky*, Koon-Kiu Yan*, Daifeng Wang*, Chao Cheng*, …, Steven Brenner, Brenton Graveley, Susan Celniker, Thomas Gingeras, and Robert Waterston, Comparative Analysis of the Transcriptome across Distant Species, Nature 512, 445–448, 2014 (News & Views, Nature)
• Alan P. Boyle*, Carlos L. Araya*, …, Daifeng Wang, …, Elise A. Feingold, Peter J. Good, Michael J. Pazin, Haiyan Huang, Peter J. Bickel, Steven E. Brenner, Valerie Reinke, Robert H. Waterston, Mark Gerstein, Kevin P. White, Manolis Kellis, Michael Snyder, Comparative analysis of regulatory information and circuits across diverse species, Nature 512, 453–456, 2014 (News & Views, Nature)
• Koon-Kiu Yan*, Daifeng Wang*, Joel Rozowsky, Henry Zheng, Mark Gerstein, OrthoClust: An orthology-based network framework for expression clustering across multiple species, Genome Biology 15:R100, 2014
• Cristina Sisu, Baikang Pei, Jing Leng, Adam Frankish, Yan Zhang, Suganthi Balasubramanian, Rachel Harte, Daifeng Wang, Michael Rutenberg Schoenberg, Wyatt Clark, Mark Diekhans, Joel Rozowsky, Tim Hubbard, Jennifer Harrow, Mark Gerstein, Comparative analysis of pseudogenes across three phyla, Proceedings of the National Academy of Sciences (PNAS), vol. 111, no. 37, pp. 13361–13366, 2014
• Daifeng Wang, Eric Pan, Gang Fang, Sunita Kumari, Fei He, Koon-Kiu Yan, Doreen Ware, Sergei Maslov, Mark Gerstein, Comparative network analysis of gene co-expression networks reveals the conserved and species-specific functions of cell-wall related genes between Arabidopsis and Poplar, Proceedings of 4th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics (ACM BCB 2013)
• Daifeng Wang, Mia K. Markey, Claus O. Wilke and Ari Arapostathis, Eigen-genomic System Dynamic-pattern Analysis (ESDA): Modeling mRNA degradation and self-regulation, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. 2, pp. 430-437, 2012
• Daifeng Wang, Ari Arapostathis, Claus O. Wilke, and Mia K. Markey, Principal-Oscillation-Pattern Analysis of Gene Expression, PLoS ONE 7(1): e28805, 2012
• Sean X. Shi, Anand Ramalingam, Daifeng Wang, and David Z. Pan, Latch Modeling for Statistical Timing Analysis, Proceedings of the IEEE Conference on Design, Automation and Test in Europe 2008
• Wei Wu, Daifeng Wang, Ari Arapostathis and K. Davey, Optimal Power Generation Scheduling of a Shipboard Power System, Proceedings of the IEEE Electric Ship Technologies Symposium 2007
• Daifeng Wang and Brian L. Evans, Codebook Design for Noncoherent MIMO Communications Via Reflection Matrices, Proceedings of the IEEE Global Telecommunications Conference 2006

Book reviews and chapters

• Justin Snider, Daifeng Wang, Daniel F. Bogenhagen, John D. Haley, Pulse SILAC Approaches to the Measurement of Cellular Dynamics,  Advances in Experimental Medicine and Biology book series (AEMB, volume 1140), pp 575-583
• Daifeng Wang, Chao Cheng, Chapter: Genomics and Systems Biology, Cooperative and Graph Signal Processing, Editors: Petar M. Djuric and Cedric Richard, Elsevier, 2018, ISBN: 978-0-12-813677-5
• Daifeng Wang, Epigenomics in Health and Disease by Mario Fraga and Agustin F. Fernandez, The Quarterly Review of Biology, 93:2, 163-164, 2018
• Daifeng Wang, Systems Biology: Constraint-Based Reconstruction and Analysis by Bernhard O. Palsson, The Quarterly Review of Biology, 92:3, 303-304, 2017