Weekly research seminar.
Organizers
- prof. dr hab. Anna Gambin
- dr Aleksander Jankowski
- dr hab. Bartosz Wilczyński, prof. ucz.
Information
Wednesdays, 10:15 a.m. , room: 3250Home page
https://bioputer.mimuw.edu.pl/seminars/bob/Research fields
List of talks
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Dec. 17, 2025, 10:15 a.m.
Jan Olszewski (MIM UW)
MATTS atom types and their use case in analyzing representations of deep neural networks
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Dec. 10, 2025, 10:15 a.m.
Simone Ciccolella (University of Milano-Bicocca)
Modelling and combinatorial approaches for Pangenomics
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Dec. 3, 2025, 10:15 a.m.
Brendonas Stakauskas (Vilnius University)
Use of Protein Language Models for Phylogenetic Analysis
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Nov. 26, 2025, 10:15 a.m.
Nicolaas Van Renne (Brussels University Hospital)
A multi-omics analysis of advanced Triple-Negative Breast Cancer identifies predictors to chemo-immunotherapy and on-treatment dynamics
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Nov. 19, 2025, 10:15 a.m.
Marcin Możejko (MIM UW)
PepCompass: Navigating peptide embedding spaces using Riemannian geometry
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Nov. 12, 2025, 10:15 a.m.
Diego Marques Coelho (Ryvu Therapeutics and Federal University of Rio Grande do Norte)
Building and breaking bridges in scRNAseq networks
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Nov. 5, 2025, 10:15 a.m.
Michał Krzysztoń (Institute of Biochemistry and Biophysics PAS)
Mind the gap – Pol II transcription between seed maturation and germination
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Oct. 29, 2025, 10:15 a.m.
Martyna Molak (CeNT UW)
Archeo- and palaeogenomics. Bioinformatic challenges in investigating the past using DNA.
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Oct. 22, 2025, 10:15 a.m.
Adam Cicherski (MIM UW)
From k-mers to Suffix Arrays: Almost Linear-Time Construction of Reference-free Pangenome Graphs
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Oct. 15, 2025, 10:15 a.m.
Eugene Baulin, Maksim Serdakov (IMol PAS)
Identifying GNRA tetraloop motifs in RNA 3D structures and in sequences
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June 11, 2025, 10:15 a.m.
Łucja Kowalewska; Szymon Nowakowski (Faculty of Biology, UW; MIM UW and Center4ML, Faculty of Physics, UW)
Automated Recognition of Membrane Nanostructural Assemblies: Neural Networks Meet Electron Microscopy
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June 4, 2025, 10:15 a.m.
Marcin Możejko (MIM UW)
Discovering Clinically Relevant Cellular Neighborhoods Using Cellohood
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