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Genome Data Science
We develop methods and tools to work with tens of thousands of genomes and analyze and integrate the corresponding data.

Model of DNA double helix in front of a student.
© Universität Bielefeld
You are here: home » teaching » 2024winter » aaibm
Advanced Artificial Intelligence in Biomedicine


392232/ 392240	Schönhuth, Knop	Winter 2024/25	Thu 12:00-14:00 X-E0-204 (S) and Thu 10:00-12:00 X-E0-204 (Ü)
:!: The exercises will start subsequent to the presentations, probably in JAN/FEB 2025

Introduction / How to present


introduction-101024.pdf
howtopresent.pdf

Papers - more follow soon


Title	Authors	Year	Journal
Sequence modeling and design from molecular to genome scale with Evo	Eric Nguyen et al.	2024	biorxiv
Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling	Yair Schiff et al.	2024	arXiv
Flow Matching for Generative Modeling	Yaron Lipman et al.	2023	arXiv
Learning single-cell perturbation responses using neural optimal transport	Charlotte Bunne et al.	2023	nature
Philip Frese	Privacy-preserving decentralized learning methods for biomedical applications	Mohammad Tajabadi et al.	2024	ScienceDirect
Integrate Any Omics: Towards genome-wide data integration for patient stratification	Shihao Ma	2024	arXiv
DeepTTA: a transformer-based model for predicting cancer drug response	Likun Jiang et al.	2022	Briefings in Bioinformatics
Henrik Folz	Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models	Rosa Lundbye Allesøe et al.	2023	Nature Biotechnology
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks	Fabian B. Fuchs et al.	2020	34th Conference on Neural Information Processing Systems (NeurIPS 2020)
DIFFDOCK: DIFFUSION STEPS, TWISTS, AND TURNS FOR MOLECULAR DOCKING	Gabriele Corso et al.	2023	ICLR
Fabian Molls	EQUIBIND: Geometric Deep Learning for Drug Binding Structure Prediction	HannesStärk et al.	2022	39th International Conference on Machine Learning
HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution	Eric Nguyen et al.	2023	NeurIPS 2023
Alexander Hüdepohl	Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help?	Zhi Chen et al.	2023	Conference on Health, Inference, and Learning (CHIL)
Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation	Hang Dong et al.	2021	Journal of Biomedical Informatics
Bhautik Lukhi	BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining	Renqian Luo et al.	2022	Briefings in Bioinformatics
Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures	Shitong Luo et al.	2022	NeurIPS
Here the list of papers and in front of it sometimes the names of people assigned to presenting them. On some noone is assigned jet and I am looking to get assigned to one of them but i dont know which is the most relevant. I know transformers well and they are highly important tell me which of the paper is a relevant additiin to the transformer indroducing new important ideas also introduce the other papers. Give me a overvuew over each of the yet unassigned papers and a rating of the relevance for me as a bioinformatics student with interesst in AI and medicine.