SPOCTOPUS: a combined predictor of signal peptides and membrane protein topology. - Håkan Viklund; Andreas Bernsel; Marcin J. Skwark; Arne Elofsson (Bioinform., 2008)

Improved predictions by Pcons.net using multiple templates. - Per Larsson; Marcin J. Skwark; Björn Wallner; Arne Elofsson (Bioinform., 2011)

PconsC: combination of direct information methods and alignments improves contact prediction. - Marcin J. Skwark; Abbi Abdel-Rehim; Arne Elofsson (Bioinform., 2013)

PconsD: ultra rapid, accurate model quality assessment for protein structure prediction. - Marcin J. Skwark; Arne Elofsson (Bioinform., 2013)

PconsFold: improved contact predictions improve protein models. - Mirco Michel; Sikander Hayat; Marcin J. Skwark; Chris Sander; Debora S. Marks; Arne Elofsson (Bioinform., 2014)

Improving Contact Prediction along Three Dimensions. - Christoph Feinauer; Marcin J. Skwark; Andrea Pagnani; Erik Aurell (PLoS Comput. Biol., 2014)

Improved Contact Predictions Using the Recognition of Protein Like Contact Patterns. - Marcin J. Skwark; Daniele Raimondi; Mirco Michel; Arne Elofsson (PLoS Comput. Biol., 2014)

Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images. - Vladimir Golkov; Marcin J. Skwark; Antonij Golkov; Alexey Dosovitskiy; Thomas Brox; Jens Meiler; Daniel Cremers (NIPS, 2016)

Predicting accurate contacts in thousands of Pfam domain families using PconsC3. - Mirco Michel; Marcin J. Skwark; David Menéndez Hurtado; Magnus Ekeberg; Arne Elofsson (Bioinform., 2017)

Mabellini: a genome-wide database for understanding the structural proteome and evaluating prospective antimicrobial targets of the emerging pathogen Mycobacterium abscessus. - Marcin J. Skwark; Pedro Henrique Monteiro Torres; Liviu Copoiu; Bridget Bannerman-Chukualim; R. Andres Floto; Tom L. Blundell (Database J. Biol. Databases Curation, 2019)

3D Deep Learning for Biological Function Prediction from Physical Fields. - Vladimir Golkov; Marcin J. Skwark; Atanas Mirchev; Georgi Dikov; Alexander R. Geanes; Jeffrey L. Mendenhall; Jens Meiler; Daniel Cremers (3DV, 2020)

Designing a Prospective COVID-19 Therapeutic with Reinforcement Learning. - Marcin J. Skwark; Nicolás López Carranza; Thomas Pierrot; Joe Phillips; Slim Said; Alexandre Laterre; Amine Kerkeni; Ugur Sahin; Karim Beguir (CoRR, 2020)

Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation. - Ian Sillitoe; Antonina Andreeva; Tom L. Blundell; Daniel W. A. Buchan; Robert D. Finn; Julian Gough; David T. Jones; Lawrence A. Kelley; Typhaine Paysan-Lafosse; Su Datt Lam; Alexey G. Murzin; Arun Prasad Pandurangan; et al. (Nucleic Acids Res., 2020)

Early computational detection of potential high-risk SARS-CoV-2 variants. - Karim Beguir; Marcin J. Skwark; Yunguan Fu; Thomas Pierrot; Nicolás López Carranza; Alexandre Laterre; Ibtissem Kadri; Abir Korched; Anna U. Lowegard; Bonny Gaby Lui; Bianca Sänger; Yunpeng Liu; et al. (Comput. Biol. Medicine, 2023)

InstaNovo enables diffusion-powered de novo peptide sequencing in large-scale proteomics experiments. - Kevin Eloff; Konstantinos Kalogeropoulos; Amandla Mabona; Oliver Morell; Rachel Catzel; Esperanza Rivera-de-Torre; Jakob Berg Jespersen; Wesley Williams; Sam P. B. van Beljouw; Marcin J. Skwark; Andreas Hougaard Laustsen; Stan J. J. Brouns; et al. (Nat. Mac. Intell., 2025)