Machine Learning for Bioinformatics/Computational Biology - To Be Added
Application of machine/deep learning to single cell RNA sequence (scRNAseq), Assay for Transposase-Accessible Chromatin using sequence (ATAC-seq), etc. Analysis of high throughput sequencing genomics data (ChIP-Seq, DNase-Seq, and/or ATAC-Seq). Deep learning, explainable AI for computational biology problems - quality control (QC) clustering, denoising, imputation, trajectory inference, immunogenicity prediction, RNA binding protein prediction, transcription factor binding prediction. Analysis of multiplexed imaging, mass spectrometry imaging (MSI), CODEX imaging, spatial transcriptomics in tandem with single-cell genomics data and in general multi-omics analysis. Exploration of latent structures in single cell data, finding common embeddings/integration for mutimodal biological data.
Single-cell: DeepImmuno, scTriangulate, MaxATAC, CellDrift (coming soon)
J. Zhang, Q. Wu, C. B. Johnson, G. Pham, J. M. Kinder, A. Olsson, A. Slaughter, M. May, B. Weinhaus, A. D'Alessandro, J. D. Engel, J. X. Jiang, J. M. Kofron, L. F. Huang, V. B. S. Prasath, S. S. Way, N. Salomonis, H. L. Grimes, D. Lucas. In situ mapping identifies distinct vascular niches for myelopoiesis. Nature, 590, 457-462, February 2021. [Clustering]
G. Li, B. Iyer, V. B. S. Prasath, Y. Ni, N. Salomonis. "DeepImmuno: Deep learning-empowered prediction and generation of immunogenic peptides for T cell immunity". Briefings in Bioinformatics, 22(6), November 2021. Code, online app. [DeepImmuno]
G. Li, B. Song, H. L. Grimes, V. B. S. Prasath, N. Salomonis. scTriangulate: Decision-level integration of multimodal single-cell data. Biorxiv:10.1101/2021.10.16.464640 [scTriangulate]
T. Cazares, F. Rizvi, B. Iyer, X. Chen, M. Kotliar, L. C. Kottyan, A. Barski, V. B. S. Prasath, M. T. Weirauch, E. R. Miraldi. maxATAC: transcription factor binding from ATAC-seq with deep neural networks. Biorxiv: [MaxATAC]