Marcin J. Skwark
Marcin J. Skwark
University of Cambridge
Verified email at
Cited by
Cited by
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 computational biology 10 (11), 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 computational biology 10 (10), 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), 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
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), 2017
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
Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation
I Sillitoe, A Andreeva, TL Blundell, DWA Buchan, RD Finn, J Gough, ...
Nucleic acids research 48 (D1), D314-D319, 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 (1), baz113, 2019
The system can't perform the operation now. Try again later.
Articles 1–20