A universal toolkit for single-cell and spatial long-read transcriptomic sequencing data

Andrey Przhibelskiy1*, Lieke Michielsen2, Careen Foord2, Iman Hajirasouliha3, Hagen U. Tilgner2 and Alexandru I. Tomescu4

1University of Helsinki

2Feil Family Brain and Mind Research Institute, Weill Cornell Medicine

3Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine of Cornell University

4Department of Computer Science, University of Helsinki,

Predicting drug synergy under realistic scenarios

Uxia Veleiro1*, David Mendez2, Noël Malod-Dognin3, Natasa Przulj4 and Mikel Hernaez5

1Mohamed bin Zayed University of Artificial Intelligence

2University of Granada

3School of Digital Public Health, Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates

4Mohamed Bin Zayed University of Artificial Intelligence

5CIMA University of Navarra

Assessment of coumarin derivatives potential as cyclooxygenase-2 inhibitors

Vladimir Vlatković1*, Katarzyna Wicha-Komsta2, Tomasz Kocki2, Łukasz Komsta3, Saša Lazović4 and Darija Obradović4

1Institute of Physics Belgrade, National Institute of the Republic of Serbia, University of Belgrade

2Institute of Medical Sciences, Faculty of Medicine, The John Paul II Catholic University of Lublin, Lublin, Poland

3Faculty of Pharmacy, Medical University of Lublin, Lublin, Poland

4Institute of Physics Belgrade, National Institute of the Republic of Serbia, University of Belgrade, Belgrade, Serbia

Analysis of total transcriptome from brain tissue of progressive multiple sclerosis patients identifies ferroptosis-related genes relevant for distinction of inactive from chronic active white mater lesions

Milan Stefanović, Ivan Jovanović, Nađa Trklja*, Jovana Kuveljić, Aleksandra Stanković and Maja Živković

Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, University of Belgrade, Department of Radiobiology and Molecular Genetics