Focus at-a-glance

Systems Biology

In biology

In human physiology and pathophysiology

Computational tools

Systems Neuroscience

State of the art

Machine Learning Overviews

A guide to machine learning for biologists in Nature Reviews

Machine Learning Overview By Steve Brunton

Deep Learning Basics: Introduction and Overview By Lex Fridman

Machine Learning in Omics

General reviews

Using machine learning approaches for multi-omics data analysis: A review

Integration strategies of multi-omics data for machine learning analysis

Single-cell transcriptomics

A hitchhiker’s guide to single-cell transcriptomics and data analysis pipelines

Algorithmic advances in machine learning for single-cell expression analysis

Machine learning and statistical methods for clustering single-cell RNA-sequencing data

Big data analytics in single-cell transcriptomics: Five grand opportunities

Multiview learning

Multiview learning for understanding functional multiomics

Multi-omic and multi-view clustering algorithms: review and cancer benchmark

Spatially resolved transcriptomics

Statistical and machine learning methods for spatially resolved transcriptomics with histology

Machine Learning in Neuroscience

“Estadística y Aprendizaje Automático” By Concha Bielza

The roles of supervised machine learning in systems neuroscience

Machine Learning in Drug Discovery

Applications of machine learning in drug discovery and development (In Nature Reviews)

Formatting biological big data for modern machine learning in drug discovery by Patrick Aloy of the Institute of Research in Biomedicine, Barcelona, Spain

Michelle Gill – Artificial Intelligence Driven Drug Discovery

Machine Learning in Clinics

Neuroimaging-based diagnosis by Juan Sahuquillo of the Hospital Vall d’Hebron Barcelona, Spain

Machine learning in precision medicine: lessons to learn