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Hi🖖🏼! I'm Daniel Osorio, a Colombian computational biologist. I work as a Senior Scientific Consultant at QIAGEN Digital Insight. I earned my doctorate in Biomedical Sciences, specializing in Biomedical Genomics and Bioinformatics, from Texas A&M University. My research focuses on developing software for high-throughput single-cell RNA-seq data analysis, gene regulatory networks, data mining, metabolic modeling, and bioactive peptides.

Daniel Osorio's Projects

beeline icon beeline

BEELINE: evaluation of algorithms for gene regulatory network inference

l1000-tnbc icon l1000-tnbc

Supporting information for "Drug combination prediction for cancer treatment using disease-specific drug response profiles and single-cell transcriptional signatures"

lcl_scrna-seq icon lcl_scrna-seq

scRNA-seq with LCLs - Three cell line samples sequenced: (1) GM12878, (2) GM18502, and (3) the 1:1 mixture of the two

manifoldwarping icon manifoldwarping

Code for the AAAI 2012 Manifold Warping paper: http://people.cs.umass.edu/~ccarey/pubs/ManifoldWarping.pdf

masterthesis icon masterthesis

Identifying proteins and metabolic pathways associated with the neuroprotective response mediated by tibolone in astrocytes under an induced inflammatory model.

milor icon milor

R package implementation of milo for testing differentially abundant neighbourhoods

mtproportion icon mtproportion

Supporting information for 'Systematic determination of the mitochondrial proportion in human and mice tissues for single-cell RNA sequencing data quality control'

peptides icon peptides

An R package to calculate indices and theoretical physicochemical properties of peptides and protein sequences.

rpanglaodb icon rpanglaodb

An R package to download and merge labeled single-cell RNA-seq data from the PanglaoDB database into a Seurat object.

scorpion icon scorpion

Supplementary information for "Population-level comparisons of gene regulatory networks modeled on high-throughput single-cell transcriptomic data"

sctransferlearning icon sctransferlearning

Supporting information for "Drug combination prioritization for cancer treatment using single-cell RNA-seq based transfer learning"

supercell icon supercell

Coarse-graining of large single-cell RNA-seq data into super-cells

undergraduatethesis icon undergraduatethesis

Analysis of potential membrane disruption and stability of antimicrobial cationic peptides by molecular dynamics simulations

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