Welcome to Daniel & Gabby’s Notebook! This website is an open resource for anyone interested in exploring and discussing AI for Science.

Here at Daniel & Gabby’s Notebook, you will find a curated selection of papers from top conferences and journals in the field, including ISMB, RECOMB, NeurIPS, ICLR, ICML, AAAI, KDD, Nature Methods, Genome Research, Bioinformatics, PNAS, and PLOS Computational Biology.

We cover a wide range of topics related to AI for Science, including but not limited to:

• Pre-training strategies for genomic sequences
• Variant effect prediction
• Genome-wide association studies
• Protein structure prediction
• Single-cell genomics
• Computational immunology
• Generative models for biology (LLMs, Diffusion Models, etc.)
• Biomedical natural language processing
• LLM Agents for scientific discovery
• Interpretability of foundation models
• Multi-modal scientific models

Daniel & Gabby’s Notebook is built on the principle of open science and collaborative learning. We encourage you to contribute to our discussion forums, share your insights, and help us build a vibrant community of researchers and practitioners interested in decoding the genome through the lens of language models.

Whether you’re a bioinformatician, computational biologist, machine learning researcher, or just curious about the intersection of biology and AI, Daniel & Gabby’s Notebook is your platform for exploration and discovery.

Join us in our mission to democratize genomic knowledge and accelerate breakthroughs in understanding the complex language written in our DNA. Together, let’s unlock the potential of AI for Science and push the boundaries of what’s possible in genomics research!