3.12.2025. 15:15h, Faculty of Mathematics (online)

Charting the Unknown: AI-Powered Classification and Discovery Across the Protein Universe

Prof. Dr. Joana Pereira

VIB Center for AI and Computational Biology and Department Cellular and Molecular Medicine, KU Leuven, Leuven, Belgium

A meeting of the Bioinformatics seminar will be held on Wednesday, December 3rd, starting at 15:15, in online classroom. Teachers and students of doctoral and master studies in computer science, mathematics, biology and other related disciplines are invited to join us.

LINK: https://zoom.us/j/2183428158?pwd=ouAZtpLrbPnOBsKjQiarS9Rh59fyqF.1

Please note that the seminar time has been moved to Wednesday, 15:15 CET this semester.

Seminar

The organizer of the seminar is BIRBI. The heads of the seminar are Prof. dr Nataša Pržulj and dr Jovana Kovačević.

26.11.2025. 15:15h, Faculty of Mathematics (online)

Computational genomics at scale: Open-source frameworks for cancer omics and gene regulation

Prof. Dr. Aziz Khan

Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, United Arab Emirates

A meeting of the Bioinformatics seminar will be held on Wednesday, November 26th, starting at 15:15, in online classroom. Teachers and students of doctoral and master studies in computer science, mathematics, biology and other related disciplines are invited to join us.

LINK: https://zoom.us/j/2183428158?pwd=ouAZtpLrbPnOBsKjQiarS9Rh59fyqF.1

Please note that the seminar time has been moved to Wednesday, 15:15 CET this semester.

Abstract

Advances in cancer research rely on scalable and reproducible computational frameworks for analyzing genomic data. This seminar will introduce open-source tools and infrastructures for interrogating diverse cancer genomes. First, I will highlight open resources for studying gene regulation and the regulatory genome. Next, I will present the scalable bioinformatics infrastructure we built at Stanford to enable reproducible, large-scale cancer genomics, supporting initiatives such as the Human Tumor Atlas Network (HTAN) and Metastasis Research Network (MetNet). Finally, I will share our recent HTAN pre-cancer colon atlas using familial adenomatous polyposis (FAP) as a model.

Lecturer

Aziz Khan is an Assistant Professor of Computational Biology at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi, where he leads the Computational Biology and Cancer Regulatory Genomics (https://khanlab.bio/) Lab. His research focuses on deciphering gene regulation and the non-coding genome in cancer and precision medicine, using scalable computational and machine learning approaches. His lab develops open-source tools and integrative frameworks to interpret large-scale, multi-omics data.

Aziz earned his PhD in Bioinformatics from Tsinghua University and completed his postdoctoral research at the University of Oslo’s NCMM. Before joining MBZUAI, he was a senior research scientist at Stanford Cancer Institute, where he led core efforts in cancer genomics infrastructure and contributed to large multi-institutional initiatives, including the Human Tumor Atlas Network (HTAN) and the Metastasis Research Network (MetNet). He has developed widely used computational resources such as JASPAR, Intervene, and UniBind, and has taught and advocated for open, transparent, and reproducible science as a Carpentries Instructor and former eLife/ASAPbio Ambassador. His work bridges AI, genomics, and systems biology, with a mission to enable reproducible, collaborative, and globally impactful science.

Seminar

The organizer of the seminar is BIRBI. The heads of the seminar are Prof. dr Nataša Pržulj and dr Jovana Kovačević.

29.10.2025. 15:15h, Faculty of Mathematics (online)

Extending AlphaFold to Non-globular Proteins: Challenges and Solutions

Dr. László Dobson

Protein Bioinformatics Research Group, Institute of Molecular Life Sciences of the Research Center for Natural Sciences, Budapest, Hungary

A meeting of the Bioinformatics seminar will be held on Wednesday, October 29th, starting at 15:15, in online classroom. Teachers and students of doctoral and master studies in computer science, mathematics, biology and other related disciplines are invited to join us.

Abstract

AlphaFold2/3 has revolutionized protein structure prediction, achieving remarkable accuracy for many globular proteins. However, as a supervised learning method, it has limitations when applied to protein families that are underrepresented in its training data, particularly those that are difficult to align, which hinders the use of residue co-variation signals. Despite the broad adoption of AlphaFold2 in hundreds of downstream applications, these limitations propagate to methods built upon it.

Membrane proteins are significantly underrepresented in the Protein Data Bank (PDB), and multiple sequence alignments (MSAs) for them are often sparse or noisy. Intrinsically disordered proteins are also challenging to align, and they are typically excluded from the training set unless they are captured in complex with structured partners. As a result, AlphaFold’s performance is suboptimal for these proteins, and its limitations can skew the predictions of downstream applications. These applications may exhibit artificially high accuracy due to data leakage or misalignment between the training and target protein datasets. We demonstrate how AlphaFold’s training set biases impact prediction quality for these proteins, and discuss strategies to mitigate these effects.

Lecturer

László Dobson received his MSc in Info-Bionics Engineering and earned his PhD in Computational Biology at the Institute of Enzymology in Budapest, focusing on the structural analysis of transmembrane proteins. During his doctoral studies, he developed the CCTOP topology prediction algorithm and the Human Transmembrane Proteome database. Following his PhD, he worked in Zoltán Gáspári’s group on postsynaptic proteins, and later joined Toby Gibson’s team at the European Molecular Biology Laboratory (EMBL), where he investigated signalling systems in Leishmania pathogens. He returned to the Institute of Enzymology in 2023 to join Gábor Tusnády’s group. His current research focuses on non-globular proteins, including membrane protein–related resources and short linear motifs.

Seminar

The organizer of the seminar is BIRBI. The heads of the seminar are Prof. dr Nataša Pržulj and dr Jovana Kovačević.