Welcome to the Bioinformatics and Biotechnology Resources Hub — a comprehensive repository designed to empower researchers, scientists, and enthusiasts in the fields of bioinformatics and biotechnology. This repository serves as a one-stop destination for a myriad of invaluable resources, ranging from insightful guides and cutting-edge research papers to informative podcasts, web tools, and efficient workflows.

As resources continue to grow, please use Ctrl-F to search for desired keywords. You can also use Ctrl - to shrink the screen and view more results.

Feel free to customize the hub according to your preferences and needs by forking the repository to your profile. If you wish to contribute to the maintenance or updates of the repository, please create a pull request.

Key Features:

1. Workflow Managers (e.g., Nextflow): Streamline computational analyses with powerful workflow managers.
2. Resources for Starting a Company: Tailored resources to navigate biotech entrepreneurship and kickstart ventures.
3. Podcasts: Stay informed and inspired with expert discussions on the latest trends and breakthroughs.
4. Informatic Tools/Languages/Workflows/Libraries: A comprehensive toolkit for bioinformatics projects, including languages and workflows.
5. Models/Softwares/Pipelines: Implement cutting-edge models, software solutions, and pipelines for advanced research.
6. Web-Tools: Curated online resources and tools to simplify and enhance bioinformatics workflows.
7. Books: Diverse collection covering various bioinformatics and biotechnology topics.
8. Blogs: Stay connected with industry trends, opinions, and insights through curated blog recommendations.
9. Blog Articles: In-depth explorations of specific topics with practical tips and insights.
10. Papers: An extensive archive of research papers spanning genomics, proteomics, and bioinformatics algorithms.
11. Tutorials/Guides: Step-by-step tutorials and guides suitable for all skill levels.
12. Wet Lab: Resources tailored to experimental research and methodologies in wet lab environments.
13. Communities/Forums/Learning Platforms: Connect, collaborate, and learn through vibrant communities, forums, and dedicated platforms.

network science by albert laszlo barabasi - http://networksciencebook.com/ [18] R. Pastor-Satorras and A.Vespignani. Epidemic spreading in scalefree networks. Physical Review Letters, 86:3200–3203, 2001.

[19] R. Albert and A.-L. Barabási. Statistical Mechanics of Complex Networks. Reviews of Modern Physics, 74: 47, 2002.

[20] H. Jeong, B. Tombor, R. Albert, Z.N. Oltvai, and A.-L. Barabási . The large-scale organization of metabolic networks. Nature, 407:651–655, 2000.

[21] H. Jeong, S. P. Mason, A.-L. Barabási, and Z.N. Oltvai. Lethality and centrality in protein networks. Nature, 411:41-42, 2001.

[22] A.-L. Barabási, and Z.N. Oltvai. Network biology: understanding the cell’s functional organization. Nature Reviews Genetics, 5:101-113, 2004.

single cell rna seq

Title	field	Link
Orchestrating Single-Cell Analysis with Bioconductor	cell	https://bioconductor.org/books/release/OSCA/
Analysis of single cell RNA-seq data	cell	https://www.singlecellcourse.org/index.html
HGNC	cell	https://www.genenames.org/
Seurat	cell	https://satijalab.org/seurat/articles/get_started
Scanpy	cell	https://scanpy.readthedocs.io/en/stable/
single cell best practices	cell	https://www.sc-best-practices.org/preamble.html
Complete single-cell RNAseq analysis walkthrough - scanpy, Advanced introduction	cell	https://www.youtube.com/watch?v=uvyG9yLuNSE&t=2561s
How to analyze single-cell RNA-Seq data in R, Detailed Seurat Workflow Tutorial	cell	https://www.youtube.com/watch?v=5HBzgsz8qyk
Using SingleR to annotate single-cell RNA-seq data	cell	https://bioconductor.org/packages/devel/bioc/vignettes/SingleR/inst/doc/SingleR.html
An introduction to the SingleCellExperiment class	cell	https://www.bioconductor.org/packages/devel/bioc/vignettes/SingleCellExperiment/inst/doc/intro.html
Introduction to Single-Cell Analysis with Bioconductor	cell	https://bioconductor.org/books/3.13/OSCA.intro/
Orchestrating Single-Cell Analysis with Bioconductor	cell	https://bioconductor.org/books/3.13/OSCA/
Assigning single-cells to known cell types with CellAssign	cell	https://irrationone.github.io/cellassign/articles/introduction-to-cellassign.html
https://www.biostars.org/p/9576725/#9576733	cell	batch effects
	cell
	cell
	cell
	cell

bulk rna seq

Title	field	Link
David PEA pathway enrichment analysis (functional annotation)	cell	https://david.ncifcrf.gov/tools.jsp
QIAGEN Ingenuity Pathway Analysis (QIAGEN IPA)	cell	https://digitalinsights.qiagen.com/products-overview/discovery-insights-portfolio/analysis-and-visualization/qiagen-ipa/
clusterprofiler	cell	https://yulab-smu.top/biomedical-knowledge-mining-book/index.html
Analyzing RNA-seq data with DESeq2	cell	https://bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html
Linear Models for Microarray and RNA-Seq Data
User’s Guide	cell	https://bioconductor.org/packages/devel/bioc/vignettes/limma/inst/doc/usersguide.pdf
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workflow managers

Title	field	Link
Nextflow	cell	https://www.nextflow.io/, https://github.com/pmb59/bioinformatics-workflows/tree/master/nextflow, https://www.nextflow.io/docs/latest/index.html, https://nf-co.re/
Galaxy	cell	https://github.com/pmb59/bioinformatics-workflows/tree/master/galaxy , https://training.galaxyproject.org/training-material/topics/introduction/tutorials/galaxy-intro-101/tutorial.html, https://training.galaxyproject.org/training-material/, https://docs.galaxyproject.org/en/master/
Snakemake	cell	https://github.com/pmb59/bioinformatics-workflows/tree/master/snakemake, https://snakemake.readthedocs.io/en/stable/tutorial/tutorial.html, https://snakemake.readthedocs.io/en/stable/
SciPipe	cell	https://github.com/pmb59/bioinformatics-workflows/tree/master/scipipe, https://scipipe.org/writing_workflows/,https://scipipe.org/
GenPipes	cell	https://github.com/pmb59/bioinformatics-workflows/tree/master/genpipes, https://genpipes.readthedocs.io/en/master/tutorials/list_tutorials.html, https://genpipes.readthedocs.io/en/master/index.html
Bpipe	cell	https://github.com/pmb59/bioinformatics-workflows/tree/master/bpipe

Resources for starting a company

Title	field	Link
biotech resources	cell	https://github.com/crazyhottommy/biotech_resource
Companies Innovating in Biotech	cell	https://www.biotech2k.com/companies/companies.html
So You Want to Start a Biotech: A Bioinformatics Approach That Works A blog post by Michele Busby.	cell	https://michelebusby.tumblr.com/post/643211974587629568/so-you-want-to-start-a-biotech-a-bioinformatics
Nextflow	cell	https://medium.com/23andme-engineering/introduction-to-nextflow-4d0e3b6768d1
How Novo Nordisk built a modern data architecture on AWS	cell	https://aws.amazon.com/blogs/big-data/how-novo-nordisk-built-a-modern-data-architecture-on-aws/
zettlr	cell	https://zettlr.com/
Modern biotech data infrastructure	cell	http://blog.booleanbiotech.com/biotech-data-infrastructure.html
The digital biotech startup playbook	cell	https://medium.com/@jfeala/the-digital-biotech-startup-playbook-398aeafca8a4
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Library repos

Title	field	Link
Bancroft Library · Oral History Center · Projects; Bioscience and Biotechnology	cell	https://www.lib.berkeley.edu/visit/bancroft/oral-history-center/projects/bioscience
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podcasts

Title	field	Link
OncoPharm: latest developments in oncology	cell	https://podcasts.apple.com/us/podcast/oncopharm/id1305345744
the long run (luke timmerman)	cell	https://podcasts.apple.com/us/podcast/the-long-run-with-luke-timmerman/id1282838969
Mendelspod (diagnostics, genetics and genomic medicine	cell	https://mendelspod.com/
STAT’s weekly biotech podcast, breaking down the latest news, digging deep into industry goings-on	cell	https://www.statnews.com/category/readout-loud/
the bioinformatics chat	cell	https://open.spotify.com/show/1adLiZOHtLtrnx6MScTvAX
	cell

Databases

Title	field	Link
uniprot	cell
IEDB	cell
uniref	cell
interpro	cell
PDB	cell
Veupathdb	cell
reactome	pathway database	https://reactome.org/
	cell

Informatic Tools/Workflows/languages

Title	field	Link
Python	cell	https://www.python.org/
R	cell	https://www.r-project.org/
Bioconductor	cell	https://www.bioconductor.org/
PyTorch: Deep learning library for python	cell	https://pytorch.org/
D3: The JavaScript library for bespokedata visualization	cell	https://d3js.org/
How to make your research data more FAIR	cell	https://howtofair.dk/
	cell
	cell

Python libraries

Title	field	Link
iFeature: generation of protein descriptors	cell	https://github.com/Superzchen/iFeature
pandas	cell
numpy	cell
rdkit	cell
pytorch	cell
tensorflow	cell
keras	cell
scikit learn	cell
	cell
	cell
	cell
	cell

R libraries

Title	field	Link
ggplate	create simple plots of biological culture plates as well as microplates.	https://github.com/jpquast/ggplate
Tidyverse	collection of R packages designed for data science	https://www.tidyverse.org/
ggplot2	graphics	https://ggplot2.tidyverse.org/
caret	set of functions that attempt to streamline the process for creating predictive models.	https://topepo.github.io/caret/
patchwork	combine separate ggplots into the same graphic	https://patchwork.data-imaginist.com/
ggstatsplot	Based Plots with Statistical Details	https://indrajeetpatil.github.io/ggstatsplot/
ggextra	collection of functions and layers to enhance ggplot2	https://cran.r-project.org/web/packages/ggExtra/vignettes/ggExtra.html
ggrepel	geoms for ggplot2 to repel overlapping text labels	https://ggrepel.slowkow.com/articles/examples.html
ggthemes	Provides 'ggplot2' themes and scales that replicate the look of plots by Edward Tufte, Stephen Few, 'Fivethirtyeight', 'The Economist', 'Stata', 'Excel', and 'The Wall Street Journal', among others	https://yutannihilation.github.io/allYourFigureAreBelongToUs/ggthemes/
clusterProfiler	A universal enrichment tool for interpreting omics data	https://bioconductor.org/packages/release/bioc/html/clusterProfiler.html, https://guangchuangyu.github.io/software/clusterProfiler/
pheatmap	A function to draw clustered heatmaps.	https://www.rdocumentation.org/packages/pheatmap/versions/1.0.12/topics/pheatmap
ComplexHeatmap	visualize associations between different sources of data sets and reveal potential patterns.	https://jokergoo.github.io/ComplexHeatmap-reference/book/
heatmaply	similar heatmaps as d3heatmap, with the advantage of speed	https://cran.r-project.org/web/packages/heatmaply/vignettes/heatmaply.html
bibliometrix	nstrument to pursue a complete bibliometric analysis, following the Science Mapping Workflow.	https://www.bibliometrix.org/home/
cowplot	simple add-on to ggplot. It provides various features that help with creating publication-quality figures,	https://cran.r-project.org/web/packages/cowplot/vignettes/introduction.html
enrichplot	visualization methods to help interpreting enrichment results	https://yulab-smu.top/biomedical-knowledge-mining-book/enrichplot.html, https://bioconductor.org/packages/release/bioc/html/enrichplot.html
bbmle	Methods and functions for fitting maximum likelihood models	https://cran.r-project.org/web/packages/bbmle/index.html
maaslin2	determining multivariable association between clinical metadata and microbial meta-omics features	https://github.com/biobakery/Maaslin2
seurat	single cell genomics, differential expression	https://satijalab.org/seurat/
deseq2	Differential gene expression analysis based on the negative binomial distribution	https://bioconductor.org/packages/release/bioc/html/DESeq2.html, https://lashlock.github.io/compbio/R_presentation.html, https://bioconductor.org/packages/devel/bioc/manuals/DESeq2/man/DESeq2.pdf, https://genviz.org/module-04-expression/0004/02/01/DifferentialExpression/, https://bioc.ism.ac.jp/packages/2.14/bioc/vignettes/DESeq2/inst/doc/beginner.pdf, https://med.und.edu/research/genomics-core/_files/docs/deseq2-handout.pdf, https://blog.bioturing.com/2022/06/02/the-basics-of-deseq2-a-powerful-tool-in-differential-expression-analysis-for-single-cell-rna-seq/, https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html, https://joey711.github.io/phyloseq-extensions/DESeq2.html
edgeR	differential expression in RNA-Seq	https://bioconductor.org/packages/release/bioc/html/edgeR.html, https://bioconductor.org/packages/devel/bioc/vignettes/Glimma/inst/doc/single_cell_edger.html
ggridges	partially overlapping line plots that create the impression of a mountain range (changes in distributions over time or space)	https://cran.r-project.org/web/packages/ggridges/vignettes/introduction.html
conflicted	provide an alternative way of resolving conflicts caused by ambiguous function names	https://www.tidyverse.org/blog/2018/06/conflicted/
ggpubr	‘ggplot2’ Based Publication Ready Plots	https://rpkgs.datanovia.com/ggpubr/
forestplot	allows for multiple confidence intervals per row, custom fonts for each text element, custom confidence intervals, text mixed with expressions, and more.	https://cran.r-project.org/web/packages/forestplot/index.html

large protein language models

Title	field	Link
ESM2	cell
protT5	cell
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models/software/pipelines

Title	field	Link
DeepFRI: Protein function prediction	cell	https://github.com/flatironinstitute/DeepFRI
MSA Transformer: Generate synthetic proteins statistically similar	https://doi.org/10.7554/eLife.79854	cell
GenProSeq: Generating Protein Sequences with Deep Generative Models	cell	GenProSeq: Generating Protein Sequences with Deep Generative Models
ESM models (META/facebook): Evolutionary Scale Modeling.	cell	cell
EvoMIL: Prediction of virus-host association. Prediction of virus-host association using protein language models and multiple instance learning	EvoMIL: Prediction of virus-host association. Prediction of virus-host association using protein language models and multiple instance learning	EvoMIL: Prediction of virus-host association. Prediction of virus-host association using protein language models and multiple instance learning
ExamPle: Explainable deep learning framework for the prediction of plant small secreted peptides.	cell	ExamPle: Explainable deep learning framework for the prediction of plant small secreted peptides.
SuMD: Supervised Molecular Dynamics Simulations.	cell	SuMD: Supervised Molecular Dynamics Simulations.
S4PRED: A tool for accurate prediction of a protein's secondary structure from only its amino acid sequence with no evolutionary information i.e. MSA required	cell	https://github.com/psipred/s4pred
LinearDesign: Algorithm for Optimized mRNA Design Improves Stability and Immunogenicity	cell	https://github.com/LinearDesignSoftware/LinearDesign
gINTomics is an R package for Multi-Omics data integration and visualization	cell	https://github.com/angelovelle96/gINTomics
GSEA	Gene Set Enrichment Analysis	https://www.gsea-msigdb.org/gsea/doc/GSEAUserGuideFrame.html
Enformer: Effective gene expression prediction from sequence by integrating long-range interactions	cell	https://www.nature.com/articles/s41592-021-01252-x
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web-tools

Title	field	Link
VOSviewer: software tool for constructing and visualizing bibliometric networks	Content Cell	VOSviewer: software tool for constructing and visualizing bibliometric networks
Consensus: Evidence-Based Answers, Faster	Content Cell
Connected papers: Explore connected papers in a visual graph	cell	Connected papers: Explore connected papers in a visual graph
enrichr	comprehensive gene set enrichment analysis web server	https://maayanlab.cloud/Enrichr/
string	Protein-Protein Interaction Networks
Functional Enrichment Analysis	https://string-db.org/
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Books

Title	field	Link
Data Analysis in Medicine and Health using R	Content Cell	https://bookdown.org/drki_musa/dataanalysis/
	Content Cell

Blogs

Title	field	Link
codon	cell	https://www.readcodon.com/
Liams' Blog	cell	https://liambai.com/
single cell best practices	cell	https://www.sc-best-practices.org/preamble.html
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Blog articles

Title	field	Link
AlphaFold 2 is here: what’s behind the structure prediction miracle	cell	https://www.blopig.com/blog/2021/07/alphafold-2-is-here-whats-behind-the-structure-prediction-miracle/
The big problems	cell	https://www.science.org/content/blog-post/big-problems
Why we didn’t get a malaria vaccine sooner	Content Cell	https://worksinprogress.co/issue/why-we-didnt-get-a-malaria-vaccine-sooner
How to represent a protein sequence	Content Cell	https://liambai.com/protein-representation/
What we can learn from evolving proteins	Content Cell	https://liambai.com/protein-evolution/
	Content Cell
	Content Cell
	Content Cell

papers

Title	field	Link
Generative models for protein structure: A comparison between Generative Adversarial and Autoregressive networks.	cell	https://webthesis.biblio.polito.it/15944/
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Tutorials/guides

Title	field	Link
Introduction to RNA-Seq using high-performance computing	Content Cell	https://hbctraining.github.io/Intro-to-rnaseq-hpc-O2/)https://hbctraining.github.io/Intro-to-rnaseq-hpc-O2/
Introduction to Single-Cell Analysis with Bioconductor	Content Cell	https://bioconductor.org/books/release/OSCA/
Orchestrating Single-Cell Analysis with Bioconductor Authors: Robert Amezquita [aut], Aaron Lun [aut], Stephanie Hicks [aut], Raphael Gottardo [aut], Alan	cell	Orchestrating Single-Cell Analysis with Bioconductor Authors: Robert Amezquita [aut], Aaron Lun [aut], Stephanie Hicks [aut], Raphael Gottardo [aut], Alan
Development of an Online Laboratory Handbook and Remote Workflow for Chemistry and Pharmacy Master’s Students to Undertake Computer-Aided Drug Design.	cell	Development of an Online Laboratory Handbook and Remote Workflow for Chemistry and Pharmacy Master’s Students to Undertake Computer-Aided Drug Design.
Contact maps	cell	Contact maps
TeachOpenCADD: Virtual screening.	cell	https://projects.volkamerlab.org/teachopencadd/all_talktorials.html, https://volkamerlab.org/projects/teachopencadd/
GROMACS tutorial	cell	http://www.mdtutorials.com/gmx/
ESM models (META/facebook): Evolutionary Scale Modeling.	cell	ESM models (META/facebook): Evolutionary Scale Modeling.
The Art of Command Line	cell	https://github.com/crazyhottommy/the-art-of-command-line
RNA-seq analysis	cell	https://github.com/crazyhottommy/RNA-seq-analysis, https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2018/RNASeq2018/html/06_Gene_set_testing.nb.html
intermediate python	cell	https://github.com/crazyhottommy/intermediatePython
gene set enrichment analysis in R	cell	https://bioinformaticsbreakdown.com/how-to-gsea/, https://brb.nci.nih.gov/BRB-ArrayTools/RPackagesAndManuals/GSEA-vignettes.html, https://rpubs.com/jrgonzalezISGlobal/enrichment, https://learn.gencore.bio.nyu.edu/rna-seq-analysis/gene-set-enrichment-analysis/ , https://www.biostars.org/p/467197/, https://sbc.shef.ac.uk/workshops/2019-01-14-rna-seq-r/rna-seq-gene-set-testing.nb.html, https://www.sc-best-practices.org/conditions/gsea_pathway.html
Reactome enrichment analysis	cell	http://yulab-smu.top/biomedical-knowledge-mining-book/reactomepa.html
Analysis of single cell RNA-seq data	cell	https://www.singlecellcourse.org/, https://hbctraining.github.io/scRNA-seq/, https://learn.gencore.bio.nyu.edu/single-cell-rnaseq/, https://training.galaxyproject.org/training-material/topics/single-cell/tutorials/scrna-intro/slides-plain.html
Next-Generation Sequencing Analysis Resources	cell	https://learn.gencore.bio.nyu.edu/
single cell best practices	cell	https://www.sc-best-practices.org/preamble.html, https://github.com/theislab/single-cell-best-practices/tree/development
Bioinformatics Education and Tutorials	cell	https://bioinformaticshome.com/bioinformatics_tutorials/tutorials_main.html, https://www.hadriengourle.com/tutorials/, https://ghtf.biochem.uci.edu/bioinformatics-tutorials/, https://www.melbournebioinformatics.org.au/tutorials/, https://libguides.marquette.edu/c.php?g=36753&p=233518, https://bioinformatics.uconn.edu/resources-and-events/tutorials-2/, https://abacus.bates.edu/bioinformatics1/, https://www.embl.org/ells/teachingbase/dna-barcoding-resource/bioinformatics-tutorials/
NAMD and VMD for molecular dynamics	cell	http://www.ks.uiuc.edu/Training/Tutorials/#namd, http://www.ks.uiuc.edu/Training/Tutorials/#vmd
NGS: illumina	cell	https://emea.illumina.com/science/technology/next-generation-sequencing/beginners/tutorials.html
Introduction to Long-Read Data Analysis	cell	https://timkahlke.github.io/LongRead_tutorials/
Galaxy Training	cell	https://training.galaxyproject.org/
bioinfo guided tutorial	cell	https://www.angelfire.com/ga2/nestsite2/bioinform.html, http://lectures.molgen.mpg.de/
Getting started with bioinformatics	cell	https://riptutorial.com/bioinformatics
Free online courses in Bioinformatics	cell	https://ethz.ch/content/dam/ethz/special-interest/biol/department/Bioinformatics%20courses.pdf
NGS alignment and variant calling	cell	https://github.com/ekg/alignment-and-variant-calling-tutorial
bioinformatics workshops	cell	https://bioinformatics.ca/workshops/previous-workshops/
SIB tutorials about bioinformatics	cell	https://edu.sib.swiss/
Microarray Analysis	cell	http://barc.wi.mit.edu/education/bioinfo2007/arrays/
Kaggle's tutorials on machine learning, deep learning, data analysis	cell	https://www.kaggle.com/learn
pytorch tutorials	cell	https://pytorch.org/tutorials/
pytorch basics	cell	https://pytorch.org/tutorials/beginner/basics/intro.html, https://pytorch.org/tutorials/beginner/pytorch_with_examples.html
ADVANCED: MAKING DYNAMIC DECISIONS AND THE BI-LSTM CRF	cell	https://pytorch.org/tutorials/beginner/nlp/advanced_tutorial.html
RNA-seq	****	https://scienceparkstudygroup.github.io/rna-seq-lesson/

Interesting labs

Title	field	Link
volkamer lab	cell	https://volkamerlab.org/research/
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wet lab

Title	field	Link
basic methods	cell	https://www.youtube.com/@csberg5856/videos
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Communities

Title	field	Link
Rosalind (forum and platform for learning bioinformatics)	cell	https://rosalind.info/problems/list-view/, solutions: https://github.com/crazyhottommy/rosalind_problems_python_solutions
biostars	cell	https://www.biostars.org/
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