Research

Publications

2018

  • Arshdeep Sekhon, R. Singh, and Yanjun Qi, “DeepDiff: Deep-learning for predicting Differential gene expression from histone modifications”, ECCB (to appear).

2017

  • R. Singh, Jack Lanchantin, Arshdeep Sekhon, and Yanjun Qi, “Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin”. NIPS. [arXiv][code]
  • R. Singh, Arshdeep Sekhon, Kamran Kowsari, Jack Lanchantin, Beilun Wang, and Yanjun Qi, “GaKCo: a Fast GApped k-mer string Kernel using COunting”. ECML-PKDD. [arXiv][code]
  • Beilun Wang, R. Singh, and Yanjun Qi, “A constrained l1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models”. Machine Learning. [paper] 
  • Jack Lanchantin, R. Singh, and Yanjun Qi. “Memory Matching Networks for Genomic Sequence Classification”. ICLR Workshop. [arXiv]
  • Jack Lanchantin, R. Singh, Beilun Wang, and Yanjun Qi. “Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks”. Pacific Symposium on Biocomputing. (PSB). [arXiv][code]

2016

  • R. Singh, Jack Lanchantin, Gabriel Robins, and Yanjun Qi. “Transfer String Kernel for Cross-Context DNA-Protein Binding Prediction”. IEEE/ACM Transactions on Computational Biology and Bioinformatics. [arXiv][code]
  • R. Singh, Jack Lanchantin, Gabriel Robins, and Yanjun Qi. “DeepChrome:  Deep-learning for predicting gene expression from histone modifications”. Bioinformatics. (ECCB). [paper][arXiv][code][website]
  • R. Singh and Yanjun Qi. “Character based String Kernels for Bio-Entity Relation Detection”. ACL BioNLP Workshop. [paper][slides]
  • Beilun Wang, R. Singh, and Yanjun Qi. “A constrained l1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models”. ICML Workshop on Computational Biology. [arXiv]
  • Jack Lanchantin, R. Singh, Zeming Lin, and Yanjun Qi.”Deep Motif: Visualizing Genomic Sequence Classifications”. ICLR and ICML Workshops on Computational Biology. [arXiv][code]

2015

  • R. Singh, Jack Lanchantin, Gabriel Robins, and Yanjun Qi. “Transfer String Kernel for Cross-Context Transcription Factor Binding Prediction”. International Workshop on Data Mining in Bioinformatics at KDD (BIOKDD). 
  • R. Singh, Cem Kuscu, Aaron Quinlan, Yanjun Qi, and Mazhar Adli.”Cas9-chromatin binding information enables more accurate CRISPR off-target prediction”. Nucleic Acid Research. [paper][website]

2014

  • Cem Kuscu, Sevki Arslan, R. Singh, Jeremy Thorpe, and Mazhar Adli. “Genome-wide analysis reveals characteristics of off-target sites bound by the Cas9 endonuclease”. Nature Biotechnology. [paper]

Collaborations

  • Peiwu Qin, Mahmut Parlak, Cem Kuscu, Jigar Bandaria, Mustafa Mir, Karol Szlachta, R. Singh, Xavier Darzcaq, Ahmet Yildiz, and Mazhar Adli. “Live cell imaging of low- and non-repetitive chromosome loci using CRISPR/Cas9”. Nature Communications (2017)
  • Aravinda Kuntimaddi, Nicholas J Achille, Jeremy Thorpe, Alyson A Lokken, R. Singh, Charles S Hemenway, Mazhar Adli, Nancy J Zeleznik-Le, John H Bushweller. “Degree of recruitment of DOT1L to MLL-AF9 defines level of H3K79 Di- and tri-methylation on target genes and transformation potential”. Cell Reports (2015)
  • Fujun Qin, Zhenguo Song, Mihaela Babiceanu, Yansu Song, Loryn Facemire, R. Singh, Mazhar Adli, Hui Li. “Discovery of CTCF-sensitive cis-spliced fusion RNAs between adjacent genes in human prostate cells”. PLOS Genetics (2015)