Michael I. Love
Michael I. Love
Associate Professor, Biostatistics & Genetics, UNC-Chapel Hill
Verified email at - Homepage
Cited by
Cited by
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
MI Love, W Huber, S Anders
Genome Biology 15 (12), 2014
Salmon provides fast and bias-aware quantification of transcript expression
R Patro, G Duggal, MI Love, RA Irizarry, C Kingsford
Nature methods 14 (4), 417-419, 2017
Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences
C Soneson, MI Love, MD Robinson
F1000Research 4, 2015
Orchestrating high-throughput genomic analysis with Bioconductor
W Huber, VJ Carey, R Gentleman, S Anders, M Carlson, BS Carvalho, ...
Nature methods 12 (2), 115-121, 2015
MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens
W Li, H Xu, T Xiao, L Cong, MI Love, F Zhang, RA Irizarry, JS Liu, ...
Genome Biology 15 (12), 554, 2014
Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences
A Zhu, JG Ibrahim, MI Love
Bioinformatics 35 (12), 2084-2092, 2019
RNA-Seq workflow: gene-level exploratory analysis and differential expression
MI Love, S Anders, V Kim, W Huber
F1000Research 4, 2015
X-exome sequencing of 405 unresolved families identifies seven novel intellectual disability genes
H Hu, SA Haas, J Chelly, H Van Esch, M Raynaud, APM de Brouwer, ...
Molecular psychiatry 21 (1), 133-148, 2016
Airway epithelial miRNA expression is altered in asthma
OD Solberg, EJ Ostrin, MI Love, JC Peng, NR Bhakta, L Hou, C Nguyen, ...
American Journal of Respiratory and Critical Care Medicine 186 (10), 965-974, 2012
Static and dynamic DNA loops form AP-1-bound activation hubs during macrophage development
DH Phanstiel, K Van Bortle, D Spacek, GT Hess, MS Shamim, I Machol, ...
Molecular cell 67 (6), 1037-1048. e6, 2017
A benchmark for RNA-seq quantification pipelines
M Teng, MI Love, CA Davis, S Djebali, A Dobin, BR Graveley, S Li, ...
Genome biology 17, 1-12, 2016
Tximeta: Reference sequence checksums for provenance identification in RNA-seq
MI Love, C Soneson, PF Hickey, LK Johnson, NT Pierce, L Shepherd, ...
PLoS computational biology 16 (2), e1007664, 2020
Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications
K Van den Berge, F Perraudeau, C Soneson, MI Love, D Risso, JP Vert, ...
Genome biology 19, 1-17, 2018
Deletions of chromosomal regulatory boundaries are associated with congenital disease
J Ibn-Salem, S Köhler, MI Love, HR Chung, N Huang, ME Hurles, ...
Genome biology 15, 1-16, 2014
Modeling of RNA-seq fragment sequence bias reduces systematic errors in transcript abundance estimation
MI Love, JB Hogenesch, RA Irizarry
Nature Biotechnology, 2016
Alignment and mapping methodology influence transcript abundance estimation
A Srivastava, L Malik, H Sarkar, M Zakeri, F Almodaresi, C Soneson, ...
Genome biology 21, 1-29, 2020
ChIP-exo signal associated with DNA-binding motifs provides insight into the genomic binding of the glucocorticoid receptor and cooperating transcription factors
SR Starick, J Ibn-Salem, M Jurk, C Hernandez, MI Love, HR Chung, ...
Genome research 25 (6), 825-835, 2015
RNA sequencing data: hitchhiker's guide to expression analysis
K Van den Berge, KM Hembach, C Soneson, S Tiberi, L Clement, MI Love, ...
Annual Review of Biomedical Data Science 2 (1), 139-173, 2019
Swimming downstream: statistical analysis of differential transcript usage following Salmon quantification
MI Love, C Soneson, R Patro
F1000Research 7, 2018
SAFE-clustering: single-cell aggregated (from ensemble) clustering for single-cell RNA-seq data
Y Yang, R Huh, HW Culpepper, Y Lin, MI Love, Y Li
Bioinformatics 35 (8), 1269-1277, 2019
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