• 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
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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

How to write reports

how to write reports.pdf

Papers - more follow soon


Date Student Title Authors Year Journal
Luca Schmidt Accurate structure prediction of biomolecular interactions with AlphaFold 3 Josh Abramson et al. 2024 nature
Lyon Brown DrugDAGT: a dual-attention graph transformer with contrastive learning improves drug-drug interaction prediction Yaojia Chen et al. 2024 BMC Biology
  MLSNet: a deep learning model for predicting transcription factor binding sites YuchuanZhang et al. 2024 Briefings in Bioinformatics
MSlocPRED: deep transfer learning-based identification of multi-label mRNA sub cellular localisation YunZuo et al. 2024 Briefings in Bioinformatics
23.01.2025 Angelica Gutu scDFN: enhancing single-cell RNA-seq clustering with Deep Fusion networks Tianxiang Liu et al. 2024 Briefings in Bioinformatics
  DeepPGD: A Deep Learning Model for DNA Methylation Prediction Using Temporal Convolution, BiLSTM, and Attention Mechanism Shoryu Teragawa et al. 2024 International Journal of Molecular Sciences
19.12.2024 Chantal Wust Biomedical literature mining: graph kernel-based learning for gene–gene interaction extraction Ai-Ru Hsieh et al. 2024  European Journal of Medical Research
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
16.01.2025 Fatih Altundas Learning single-cell perturbation responses using neural optimal transport Charlotte Bunne et al. 2023 nature
09.01.2025 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
28.11.2024 Racha Bekhouche 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
21.11.2024 Fabian Molls EQUIBIND: Geometric Deep Learning for Drug Binding Structure Prediction HannesStärk et al. 2022 39th International Conference on Machine Learning
05.12.2024 Felix Dyck HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution Eric Nguyen et al. 2023 NeurIPS 2023
19.12.2024 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)
16.01.2025 Joyce Abigail Funk 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
21.11.2024 Bhautik Lukhi BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining Renqian Luo et al. 2022 Briefings in Bioinformatics
12.12.2024 Ismail Ceyhan Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures Shitong Luo et al. 2022 NeurIPS

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