Your ask is specific; so, I may provide a specific answer:

Books:

• "Integrative Approaches for Understanding OMICS Data": https://www.amazon.com/Omics-Approaches-Technologies-Applications-Understanding/dp/9811329249
• "Deep Learning in Omics Data Analysis and Precision Medicine": https://www.ncbi.nlm.nih.gov/books/NBK550335/

GitHub Repos (R/Python):

• bioFAM/MOFA: https://github.com/bioFAM/MOFA
• RasmussenLab/MOVE: https://github.com/RasmussenLab/MOVE
• fraenkel-lab/OmicsIntegrator: https://github.com/fraenkel-lab/OmicsIntegrator
• cwieder/PathIntegrate: https://github.com/cwieder/PathIntegrate
• BiomedSciAI/Geno4SD: https://github.com/BiomedSciAI/Geno4SD

YouTube Tutorials:

• "R/Python for Biomedical Data Analysis": youtube.com/watch?v=dIJ_8cw4l84
• "OmicsLogic Training in Biomedical Data Analysis using R & Python": youtube.com/watch?v=umwgjiN4LKs

Online Courses/Tutorials:

• Survive with Omics: https://ocbe-uio.github.io/survomics/
• de.NBI: Advanced quantitative proteomics in R: https://www.denbi.de/online-training-media-library/1173-advanced-analysis-of-quantitative-proteomics-data-using-r
• Babraham Bioinformatics: RNA-Seq Analysis (DESeq), Proteomics Intro (MSstats), Statistical Analysis using R: https://www.bioinformatics.babraham.ac.uk/training/RNASeq_Course/RNA-Seq_analysis_course.pdf
• ISCB Tutorial: Machine learning for omics data (R): https://www.iscb.org/ismbeccb2025/programme-agenda/tutorials

Kind regards,

Kevin