Keep up with what's happening in Bioinformatics and Machine Learning (＾ω＾)
Last update: 04/29/2020
By: Huitian (Yolanda) Diao
<2020> Gene regulatory network reconstruction using single-cell RNA sequencing of barcoded genotypes in diverse environments
Publisher: eLife | Group: David Gresham | Institute: NYU
<2020> SimiC: a single cell gene regulatory network inference method with similarity constraints
Publisher: bioRxiv | Group: Mikel Hernaez | Institute: UIUC
<2020> Comparative single-cell trajectory network enrichment identifies pseudo-temporal systems biology patterns in hematopoiesis and CD8 T-cell development
Publisher: bioRxiv | Group: Jan Baumbach | Institute: University of Southern Denmark
<2020> Imputing single-cell RNA-seq data by combining graph convolution and autoencoder neural networks
Publisher: bioRxiv | Group: Yuedong Yang | Institute: Sun Yet-sen University
<2020> scTenifoldNet: a machine learning workflow for constructing and comparing transcriptome-wide gene regulatory networks from single-cell data
Publisher: bioRxiv | Group: James J. Cai | Institute: TAMU
<2020> CellOracle: Dissecting cell identity via network inference and in sillico gene perturbation
Publisher: bioRxiv | Group: Samantha A. Morris | Institute: WUSTL
<2020> Scedar: a scalable python package for single-cell RNA-seq exploratory data analysis
Publisher: Plos Computational Biology | Group: Deanne M. Taylor | Institute: U Penn
<2020> scLM: automatic detection of consensus gene clusters across multiple single-cell datasets
Publisehr: bioRxiv | Group: Wei Zhang | Institute: Wake Forest School of Medicine
<2020> Benchmarking algorithms for gene regulatory network inference from single-cell transcriptomic data
Publisher: Nature Methods | Group: T. M. Murali | Institute: Virginia Tech
<2020> Revealing dynamics of gene expression variability in cell state space
Publisehr: Nature Methods | Group: Dominic Grun | Institute: University of Freiburg
<2020> Towards inferring causal gene regulatory networks from single cell expression measurements
Publisher: bioRxiv | Group: Sreeram Kannan | Institute: UW
<2020> Inferring causal gene regulatory networks from coupled single-cell expression dynamics using Scribe Publisehr: Cell Systems | Group: Sreeram Kannan | Institute: UW