Compilation of interesting links on the areas that I am interested in.
Blogroll
Causal Analysis in Theory and Practice
Statistical Modeling, Causal Inference, and Social Science
inFERENCe
R Programming
Courses
Programming with R at Software Carpentry
Data Analysis and Visualization in R for Ecologists at Data Carpentry
R for Social Scientists at Data Carpentry
Online learning R at RStudio
Learn R at Hackr.io
Learn R at Kaggle
Bioinformatics
Courses
Rosalind
Path to a free self-taught education in Bioinformatics! on Ossu’s repository
An Introduction To Applied Bioinformatics on Applied-bioinformatics’ repository
Other
List compiled by Inge Jonassen
Another list at Bioinformatics.ca
Papers on Machine Learning and Bioinformatics from here.
Genomics
- Coding Region Identification (http://bit.ly/1IRU7ea)
- Gene Function Comparison (http://bit.ly/1LiknBN)
- Gene Function Prediction (http://bit.ly/1BrpLPC)
- RNA Gene Finding (http://bit.ly/1RdY8LG)
- Alternative Splicing (http://bit.ly/1LikGfO)
- Sequence Assembly (http://bit.ly/1GTFpne)
- Splice Site Prediction (http://bit.ly/1Fq0aSe)
- TF Binding (http://bit.ly/1eskz3U)
- Promoter Binding (http://bit.ly/1d4MRQl)
- Operon (http://bit.ly/1IRUXHE)
- Single Nucleotide Polymorphism (http://bit.ly/1G8Ytdy)
- RNA Structure Prediction (http://bit.ly/1H22QN7)
Proteomics
- Protein Function Prediction (http://bit.ly/1IRW8Hd)
- Protein Location Prediction (http://bit.ly/1d4OAoU)
- Protein Structure Prediction (http://bit.ly/1HZzgqv)
- Protein-Protein Interaction (http://bit.ly/1Re1Kh1)
Text Mining
- Word Disambiguation (http://bit.ly/1InymjD)
- Protein Annotation (http://bit.ly/1MQn6zD)
- Gene Annotation (http://bit.ly/1GkIs3s)
Systems Biology
- Signaling Networks (http://bit.ly/1Tz9q1c)
- Metabolic Pathways (http://bit.ly/1GTJpo0)
- Genetic Networks (http://bit.ly/1H244rG)
Microarray
- Microarray Data Analysis (http://bit.ly/1LinqtN)
- Microarray Data Preprocessing (http://bit.ly/1LinrOn)
- Microarray Image Analysis (http://bit.ly/1CfYvi0)
Causal Inference Analysis
Courses, classes and talks
A Crash Course in Causality on Coursera by Jason Roy
Causal Diagrams: Draw Your Assumptions Before Your Conclusions by Miguel Hernán
Causal Inference Bootcamp on YouTube by Matt Masten
Causality on YouTube by Jonas Peters
Causal Graphs by Julian Schüssler
Causal Data Science with Directed Acyclic Graphs by Paul Hünermund
Books
The Book of Why by Judea Pearl et al
Causal Inference in Statistics – A Primer by Judea Pearl et al
Causality: Models, Reasoning and Inference by Judea Pearl et al
Causal Inference Book by Miguel Hernan et al
Elements of Causal Inference by Jonas Peters et al
Conferences
Conference on Neural Information Processing Systems (12/2019)
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (09/2019)
ACM SIGKDD Workshop on Causal Discovery (08/2019)
AAAI Spring Symposium (03/2019)
European Causal Inference Meeting (EuroCIM) (03/2019)
Scientific Writing
Books and articles
Writing guide by Jordan Peterson
A guide for scientific writing by Utrecht University
Successful scientific writing by Janice and Robert Matthews
A Guide to Quantitative Writing in the Health Sciences by Steve Luby and Dorothy Southern
Science Research Writing for Non-Native Speakers of English by Hilary Glasman-Deal
Productivity
Work Productivity Tips: Get More Done In Less Time at CustomLogoCases.