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Title: GitHub - Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery: A collection of resources useful for leveraging big data and AI for drug discovery. It mainly serves as an orientation for new lab folks. It may be biased towards my lab interest.

Open Graph Title: GitHub - Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery: A collection of resources useful for leveraging big data and AI for drug discovery. It mainly serves as an orientation for new lab folks. It may be biased towards my lab interest.

X Title: GitHub - Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery: A collection of resources useful for leveraging big data and AI for drug discovery. It mainly serves as an orientation for new lab folks. It may be biased towards my lab interest.

Description: A collection of resources useful for leveraging big data and AI for drug discovery. It mainly serves as an orientation for new lab folks. It may be biased towards my lab interest. - Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery

Open Graph Description: A collection of resources useful for leveraging big data and AI for drug discovery. It mainly serves as an orientation for new lab folks. It may be biased towards my lab interest. - Bin-Chen-Lab/Aw...

X Description: A collection of resources useful for leveraging big data and AI for drug discovery. It mainly serves as an orientation for new lab folks. It may be biased towards my lab interest. - Bin-Chen-Lab/Aw...

Opengraph URL: https://github.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery

X: @github

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https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#introduction-to-bioinformaticscheminformatics
An Introduction to Statistical Learninghttp://www-bcf.usc.edu/~gareth/ISL/
Machine Learning course at Courserahttps://www.coursera.org/learn/machine-learning
R & Bioconductor Manualhttp://manuals.bioinformatics.ucr.edu/home/R_BioCondManual/
https://statquest.org/video-index/https://statquest.org/video-index/
HT Sequence Analysis with R and Bioconductorhttp://manuals.bioinformatics.ucr.edu/home/ht-seq
ChemmineR: Cheminformatics Toolkit for Rhttp://www.bioconductor.org/packages/devel/bioc/vignettes/ChemmineR/inst/doc/ChemmineR.html
Step by Step to practice deep learninghttp://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html
Introduction to Bioinformatics and Computational Biologyhttps://liulab-dfci.github.io/bioinfo-combio/
HarvardX Biomedical Data Science Open Online Traininghttp://rafalab.github.io/pages/harvardx.html
Statistics for biologists from StatQuesthttps://statquest.org/video-index/
Data Science Cheat Sheethttps://github.com/Bin-Chen-Lab/BigData_AI_DrugDiscovery/blob/master/data_science_cheatsheet.pdf
oscahttps://osca.bioconductor.org/introduction.html
seurathttps://satijalab.org/seurat/vignettes.html
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#fundamental-papers
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#field-review
Hallmarks of Cancer: The Next Generationhttp://www.cell.com/abstract/S0092-8674%2811%2900127-9
Tumor Metastasis: Molecular Insights and Evolving Paradigmshttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3261217/
Cancer genome landscapeshttp://science.sciencemag.org/content/339/6127/1546.long
Cancer transcriptome profiling at the juncture of clinical translationhttps://www.nature.com/articles/nrg.2017.96
Ewing sarcoma: historical perspectives, current state-of-the-art, and opportunities for targeted therapy in the future.https://www.ncbi.nlm.nih.gov/pubmed/18525337
Opportunities and challenges in phenotypic drug discovery: an industry perspectivehttps://www.nature.com/nrd/journal/v16/n8/abs/nrd.2017.111.html
Ten Years of Pathway Analysis: Current Approaches and Outstanding Challengeshttp://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002375
Deep learninghttps://www.nature.com/nature/journal/v521/n7553/full/nature14539.html
High-performance medicine: the convergence of human and artificial intelligencehttps://www.nature.com/articles/s41591-018-0300-7
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#statistical-method-development
Significance analysis of microarrays applied to the ionizing radiation responsehttp://www.pnas.org/content/98/9/5116.full
limma: Linear Models for Microarray Datahttps://link.springer.com/chapter/10.1007/0-387-29362-0_23
Differential expression analysis for sequence count datahttps://genomebiology.biomedcentral.com/articles/10.1186/gb-2010-11-10-r106
Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profileshttp://www.pnas.org/content/102/43/15545.long
Adjusting batch effects in microarray expression data using Empirical Bayes methodshttps://academic.oup.com/biostatistics/article/8/1/118/252073/Adjusting-batch-effects-in-microarray-expression
Emergence of Scaling in Random Networkshttp://science.sciencemag.org/content/286/5439/509.full
Pathsim: Meta path-based top-k similarity search in heterogeneous information networkshttp://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.220.2455
MuSiC: Identifying mutational significance in cancer genomeshttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3409272/
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#informatics-method-development-and-application
The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease.http://science.sciencemag.org/content/313/5795/1929.long
Discovery and Preclinical Validation of Drug Indications Using Compendia of Public Gene Expression Datahttp://stm.sciencemag.org/content/3/96/96ra77
Relating protein pharmacology by ligand chemistryhttp://www.nature.com/nbt/journal/v25/n2/full/nbt1284.html
Characterization of drug-induced transcriptional modules: towards drug repositioning and functional understandinghttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3658274/
Cross-Species Regulatory Network Analysis Identifies a Synergistic Interaction between FOXM1 and CENPF that Drives Prostate Cancer Malignancyhttp://www.cell.com/cancer-cell/fulltext/S1535-6108(14)00125-1
Elucidating compound mechanism of action by network perturbation analysishttp://www.sciencedirect.com/science/article/pii/S0092867415006996
Discovery of drug mode of action and drug repositioning from transcriptional responseshttp://www.pnas.org/content/107/33/14621.long
Imagenet classification with deep convolutional neural networkshttp://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#computational-analysis
Drug-target networkhttps://www.nature.com/nbt/journal/v25/n10/full/nbt1338.html
Comprehensive molecular portraits of human breast tumourshttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3465532/
Mutational landscape and significance across 12 major cancer types.http://dx.doi.org/10.1038/nature12634
Comprehensive Characterization of Molecular Differences in Cancer between Male and Female Patientshttp://www.cell.com/cancer-cell/fulltext/S1535-6108(16)30111-8
Genetics of rheumatoid arthritis contributes to biology and drug discovery.https://www.nature.com/nature/journal/v506/n7488/full/nature12873.html
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivityhttps://www.nature.com/nature/journal/v483/n7391/full/nature11003.html
A comprehensive time-course–based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene sethttp://stm.sciencemag.org/content/7/287/287ra71.short
Prediction of biological targets for compounds using multiple-category Bayesian models trained on chemogenomics databaseshttp://pubs.acs.org/doi/10.1021/ci060003g
Do structurally similar molecules have similar biological activityhttps://dx.doi.org/10.1021/jm020155c
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#deep-learning-based-drug-discovery
Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cellshttps://pubmed.ncbi.nlm.nih.gov/33096023/
A Deep Learning Approach to Antibiotic Discoveryhttps://pubmed.ncbi.nlm.nih.gov/32084340/
Deep reinforcement learning for de novo drug designhttp://advances.sciencemag.org/content/4/7/eaap7885
Convolutional Networks on Graphs for Learning Molecular Fingerprintshttps://arxiv.org/abs/1509.09292
Automatic Chemical Design Using a Data-Driven Continuous Representation of Moleculeshttps://pubs.acs.org/doi/full/10.1021/acscentsci.7b00572
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#shape-our-future
Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastomahttp://science.sciencemag.org/content/344/6190/1396
Single-cell transcriptomics uncovers distinct molecular signatures of stem cells in chronic myeloid leukemiahttps://www.nature.com/nm/journal/v23/n6/full/nm.4336.html
Brown Adipogenic Reprogramming Induced by a Small Moleculehttp://www.sciencedirect.com/science/article/pii/S2211124716317697
Correlating chemical sensitivity and basal gene expression reveals mechanism of action.https://www.nature.com/nchembio/journal/v12/n2/full/nchembio.1986.html
A Next Generation Connectivity Map: L1000 Platform And The First 1,000,000 Profileshttps://www.biorxiv.org/content/early/2017/05/10/136168
Integrative clinical genomics of metastatic cancerhttp://www.nature.com/nature/journal/v548/n7667/full/nature23306.html
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networkshttps://arxiv.org/pdf/1703.10593.pdf
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#outstanding-tools-and-datasets-for-translational-drug-discovery
Harnessing big ‘omics’ data and AI for drug discovery in hepatocellular carcinomahttps://www.nature.com/articles/s41575-019-0240-9
Leveraging big data to transform target selection and drug discoveryhttp://www.ncbi.nlm.nih.gov/pubmed/26659699
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#diseasespatients
ClinicalTrials.govhttps://clinicaltrials.gov
Cancer Today (Globocan): Data visualization tools that present current national estimates of cancer incidence, mortality, and prevalencehttp://gco.iarc.fr/today/home
UK Biobankhttp://www.ukbiobank.ac.uk/
UK Biobank Enginehttps://biobankengine.stanford.edu/
COSMIChttp://cancer.sanger.ac.uk/cosmic
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#target-discovery
cBioPortalhttp://www.cbioportal.org/
GTExhttp://www.gtexportal.org
The Human Protein Atlashttps://www.proteinatlas.org/
Cancer Cell Line Encyclopediahttps://portals.broadinstitute.org/ccle
Project Achilleshttps://portals.broadinstitute.org/achilles
DepMaphttps://depmap.org/portal/
GEOhttps://www.ncbi.nlm.nih.gov/geo/
Enrichrhttp://amp.pharm.mssm.edu/Enrichr/
STRING DBhttps://string-db.org/
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#drug-discovery
PubChemhttps://pubchem.ncbi.nlm.nih.gov/
DrugBankhttps://www.drugbank.ca/
SEAhttp://sea.bkslab.org/
LINCShttps://clue.io/
ChemMinehttp://chemmine.ucr.edu/
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#ngs-analysis
RNASEQ bloghttp://www.rna-seqblog.com/
RPKM, FPKM and TPM, clearly explainedhttp://www.rna-seqblog.com/rpkm-fpkm-and-tpm-clearly-explained/
RNA-seq workflow: gene-level exploratory analysis and differential expressionhttp://www.bioconductor.org/help/workflows/rnaseqGene/
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#python-packages
anacondahttps://anaconda.org/
scikit: a popular python machine learning packageshttp://scikit-learn.org/stable/
rdkithttp://www.rdkit.org/docs/index.html
PyTorchhttp://pytorch.org/
https://patch-diff.githubusercontent.com/Bin-Chen-Lab/Awesome_BigData_AI_DrugDiscovery#rbioconductor-packages
ggplot cheatsheethttp://zevross.com/blog/2014/08/04/beautiful-plotting-in-r-a-ggplot2-cheatsheet-3/
ChemmineR: Cheminformatics Toolkit for Rhttp://www.bioconductor.org/packages/devel/bioc/vignettes/ChemmineR/inst/doc/ChemmineR.html
biomaRthttp://bioconductor.org/packages/release/bioc/html/biomaRt.html
GEOqueryhttp://bioconductor.org/packages/release/bioc/html/GEOquery.html
cgdsrhttps://cran.r-project.org/web/packages/cgdsr/index.html
pheatmaphttps://cran.r-project.org/web/packages/pheatmap/index.html
Easy Way to Mix Multiple Graphs on The Same Pagehttp://www.sthda.com/english/articles/24-ggpubr-publication-ready-plots/81-ggplot2-easy-way-to-mix-multiple-graphs-on-the-same-page/
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