Marcin J. Skwark
Marcin J. Skwark
University of Cambridge
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SPOCTOPUS: a combined predictor of signal peptides and membrane protein topology
H Viklund, A Bernsel, M Skwark, A Elofsson
Bioinformatics 24 (24), 2928-2929, 2008
Improved contact predictions using the recognition of protein like contact patterns
MJ Skwark, D Raimondi, M Michel, A Elofsson
PLoS Comput Biol 10 (11), e1003889, 2014
PconsFold: improved contact predictions improve protein models
M Michel, S Hayat, MJ Skwark, C Sander, DS Marks, A Elofsson
Bioinformatics 30 (17), i482-i488, 2014
Improving contact prediction along three dimensions
C Feinauer, MJ Skwark, A Pagnani, E Aurell
PLoS Comput Biol 10 (10), e1003847, 2014
PconsC: combination of direct information methods and alignments improves contact prediction
MJ Skwark, A Abdel-Rehim, A Elofsson
Bioinformatics 29 (14), 1815-1816, 2013
Assessment of global and local model quality in CASP8 using Pcons and ProQ
P Larsson, MJ Skwark, B Wallner, A Elofsson
Proteins: Structure, Function, and Bioinformatics 77 (S9), 167-172, 2009
Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis
MJ Skwark, NJ Croucher, S Puranen, C Chewapreecha, M Pesonen, ...
PLoS genetics 13 (2), e1006508, 2017
Predicting accurate contacts in thousands of Pfam domain families using PconsC3
M Michel, MJ Skwark, D MenÚndez Hurtado, M Ekeberg, A Elofsson
Bioinformatics 33 (18), 2859-2866, 2017
PconsD: ultra rapid, accurate model quality assessment for protein structure prediction
MJ Skwark, A Elofsson
Bioinformatics 29 (14), 1817-1818, 2013
Discoidin domain receptor 1 kinase activity is required for regulating collagen IV synthesis
CM Borza, Y Su, TL Tran, L Yu, N Steyns, KJ Temple, MJ Skwark, J Meiler, ...
Matrix Biology 57, 258-271, 2017
Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images
V Golkov, MJ Skwark, D Alexey, T Brox, J Meiler, D Cremers
Advances in Neural Information Processing Systems, 730-738, 2016
Improved predictions by Pcons. net using multiple templates
P Larsson, MJ Skwark, B Wallner, A Elofsson
Bioinformatics 27 (3), 426-427, 2011
Membrane remodeling capacity of a vesicle‐inducing glycosyltransferase
C Ge, J Gˇmez‐Llobregat, MJ Skwark, JM Ruysschaert, ┼ Wieslander, ...
The FEBS journal 281 (16), 3667-3684, 2014
Membrane protein shaving with thermolysin can be used to evaluate topology predictors
M Bendz, M Skwark, D Nilsson, V Granholm, S Cristobal, L Kńll, ...
Proteomics 13 (9), 1467-1480, 2013
3d deep learning for biological function prediction from physical fields
V Golkov, MJ Skwark, A Mirchev, G Dikov, AR Geanes, J Mendenhall, ...
arXiv preprint arXiv:1704.04039, 2017
Ins and outs of the Bacillus subtilis membrane proteome
JM van Dijl, A Dreisbach, MJ Skwark, MJJB Sibbald, H Tjalsma, ...
Caister Academic Press, 2012
Mycobacterial genomics and structural bioinformatics: opportunities and challenges in drug discovery
VP Waman, SC Vedithi, SE Thomas, BP Bannerman, A Munir, MJ Skwark, ...
Emerging Microbes & Infections 8 (1), 109-118, 2019
Membrane protein contact and structure prediction using co-evolution in conjunction with machine learning
PL Teixeira, JL Mendenhall, S Heinze, B Weiner, MJ Skwark, J Meiler
PloS one 12 (5), e0177866, 2017
Computational saturation mutagenesis to predict structural consequences of systematic mutations in the beta subunit of RNA polymerase in Mycobacterium leprae
SC Vedithi, CHM Rodrigues, S Portelli, MJ Skwark, M Das, DB Ascher, ...
Computational and structural biotechnology journal 18, 271-286, 2020
Mabellini: a genome-wide database for understanding the structural proteome and evaluating prospective antimicrobial targets of the emerging pathogen Mycobacterium abscessus
MJ Skwark, PHM Torres, L Copoiu, B Bannerman, RA Floto, TL Blundell
Database 2019, baz113, 2019
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