Architecture of the human regulatory network derived from ENCODE data von Gerstein, Mark B., Kundaje, Anshul, Hariharan, Manoj, Landt, Stephen G., Yan, Koon-Kiu, Cheng, Chao, Mu, Xinmeng Jasmine, Khurana, Ekta, Rozowsky, Joel, Alexander, Roger, Min, Renqiang, Alves, Pedro, Abyzov, Alexej, Addleman, Nick, Bhardwaj, Nitin, Boyle, Alan P., Cayting, Philip, Charos, Alexandra, Chen, David Z., Cheng, Yong, Clarke, Declan, Eastman, Catharine, Euskirchen, Ghia, Frietze, Seth, Fu, Yao, Gertz, Jason, Grubert, Fabian, Harmanci, Arif, Jain, Preti, Kasowski, Maya, Lacroute, Phil, Leng, Jing, Lian, Jin, Monahan, Hannah, O’Geen, Henriette, Ouyang, Zhengqing, Partridge, E. Christopher, Patacsil, Dorrelyn, Pauli, Florencia, Raha, Debasish, Ramirez, Lucia, Reddy, Timothy E., Reed, Brian, Shi, Minyi, Slifer, Teri, Wang, Jing, Wu, Linfeng, Yang, Xinqiong, Yip, Kevin Y., Zilberman-Schapira, Gili, Batzoglou, Serafim, Sidow, Arend, Farnham, Peggy J., Myers, Richard M., Weissman, Sherman M., Snyder, Michael

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Systematic exploration of essential yeast gene function with temperature-sensitive mutants von Andrews, Brenda, Boone, Charles, Li, Zhijian, Vizeacoumar, Franco J, Bahr, Sondra, Li, Jingjing, Warringer, Jonas, Vizeacoumar, Frederick S, Min, Renqiang, VanderSluis, Benjamin, Bellay, Jeremy, DeVit, Michael, Fleming, James A, Stephens, Andrew, Haase, Julian, Lin, Zhen-Yuan, Baryshnikova, Anastasia, Lu, Hong, Yan, Zhun, Jin, Ke, Barker, Sarah, Datti, Alessandro, Giaever, Guri, Nislow, Corey, Bulawa, Chris, Myers, Chad L, Costanzo, Michael, Gingras, Anne-Claude, Zhang, Zhaolei, Blomberg, Anders, Bloom, Kerry

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TIP: A probabilistic method for identifying transcription factor target genes from ChIP-seq binding profiles von Cheng, Chao, Min, Renqiang, Gerstein, Mark

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Understanding transcriptional regulation by integrative analysis of transcription factor binding data von Cheng, Chao, Alexander, Roger, Min, Renqiang, Leng, Jing, Yip, Kevin Y, Rozowsky, Joel, Yan, Koon-Kiu, Dong, Xianjun, Djebali, Sarah, Ruan, Yijun, Davis, Carrie A, Carninci, Piero, Lassman, Timo, Gingeras, Thomas R, Guigó, Roderic, Birney, Ewan, Weng, Zhiping, Snyder, Michael, Gerstein, Mark

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On TCR binding predictors failing to generalize to unseen peptides von Grazioli, Filippo, Mösch, Anja, Machart, Pierre, Li, Kai, Alqassem, Israa, O'Donnell, Timothy J, Min, Martin Renqiang

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Gene expression variability within and between human populations and implications toward disease susceptibility von Li, Jingjing, Liu, Yu, Kim, Taehyung, Min, Renqiang, Zhang, Zhaolei

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High-order neural networks and kernel methods for peptide-MHC binding prediction von Kuksa, Pavel P, Min, Martin Renqiang, Dugar, Rishabh, Gerstein, Mark

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A deep generative model for molecule optimization via one fragment modification von Chen, Ziqi, Min, Martin Renqiang, Parthasarathy, Srinivasan, Ning, Xia

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Ranking-Based Convolutional Neural Network Models for Peptide-MHC Class I Binding Prediction von Chen, Ziqi, Min, Martin Renqiang, Ning, Xia

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Accelerating deep neural network training with inconsistent stochastic gradient descent von Wang, Linnan, Yang, Yi, Min, Renqiang, Chakradhar, Srimat

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Exploiting the determinants of stochastic gene expression in Saccharomyces cerevisiae for genome-wide prediction of expression noise von Li, Jingjing, Min, Renqiang, Vizeacoumar, Franco J., Jin, Ke, Xin, Xiaofeng, Zhang, Zhaolei, Li, Wen-Hsiung

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Parametric t-Distributed Stochastic Exemplar-Centered Embedding von Renqiang Min, Martin, Guo, Hongyu, Shen, Dinghan

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Model-based autoencoders for imputing discrete single-cell RNA-seq data von Tian, Tian, Min, Martin Renqiang, Wei, Zhi

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Predicting spatially resolved gene expression via tissue morphology using adaptive spatial GNNs von Song, Tianci, Cosatto, Eric, Wang, Gaoyuan, Kuang, Rui, Gerstein, Mark, Min, Martin Renqiang, Warrell, Jonathan

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Impeller: a path-based heterogeneous graph learning method for spatial transcriptomic data imputation von Duan, Ziheng, Riffle, Dylan, Li, Ren, Liu, Junhao, Min, Martin Renqiang, Zhang, Jing

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DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays von Chen, Zhanlin, Zhang, Jing, Liu, Jason, Dai, Yi, Lee, Donghoon, Min, Martin Renqiang, Xu, Min, Gerstein, Mark

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Attentive Variational Information Bottleneck for TCR–peptide interaction prediction von Grazioli, Filippo, Machart, Pierre, Mösch, Anja, Li, Kai, Castorina, Leonardo V, Pfeifer, Nico, Min, Martin Renqiang

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Binding peptide generation for MHC Class I proteins with deep reinforcement learning von Chen, Ziqi, Zhang, Baoyi, Guo, Hongyu, Emani, Prashant, Clancy, Trevor, Jiang, Chongming, Gerstein, Mark, Ning, Xia, Cheng, Chao, Min, Martin Renqiang

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DECODE: a De ep-learning framework for Co n de nsing enhancers and refining boundaries with large-scale functional assays von Chen, Zhanlin, Zhang, Jing, Liu, Jason, Dai, Yi, Lee, Donghoon, Min, Martin Renqiang, Xu, Min, Gerstein, Mark

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Gene Expression Variability within and between Human Populations and Implications toward Disease Susceptibility: e1000910 von Li, Jingjing, Liu, Yu, Kim, TaeHyung, Min, Renqiang, Zhang, Zhaolei

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