Martin Steinegger
Martin Steinegger
Verified email at snu.ac.kr
Title
Cited by
Cited by
Year
MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets
M Steinegger, J Söding
Nature biotechnology 35 (11), 1026-1028, 2017
4172017
Clustering huge protein sequence sets in linear time
M Steinegger, J Söding
Nature communications 9 (1), 1-8, 2018
1652018
HH-suite3 for fast remote homology detection and deep protein annotation
M Steinegger, M Meier, M Mirdita, H Vöhringer, SJ Haunsberger, J Söding
BMC Bioinformatics 20, 2019
1632019
Uniclust databases of clustered and deeply annotated protein sequences and alignments
M Mirdita, L von den Driesch, C Galiez, MJ Martin, J Söding, M Steinegger
Nucleic Acids Research, 2016
1542016
ProtTrans: Towards Cracking the Language of Life’s Code Through Self-Supervised Deep Learning and High Performance Computing
A Elnaggar, M Heinzinger, C Dallago, G Rehawi, Y Wang, L Jones, ...
biorxiv, 2020
65*2020
Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold
M Steinegger, M Mirdita, J Söding
Nature Methods 16, 603–606, 2019
572019
High accuracy protein structure prediction using deep learning
J Jumper, R Evans, A Pritzel, T Green, M Figurnov, K Tunyasuvunakool, ...
Fourteenth Critical Assessment of Techniques for Protein Structure …, 2020
562020
MMseqs software suite for fast and deep clustering and searching of large protein sequence sets
M Hauser, M Steinegger, J Söding
Bioinformatics 32 (9), 1323-1330, 2016
522016
Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank
M Steinegger, SL Salzberg
Genome Biology 21, 2020
402020
Protein sequence analysis using the MPI bioinformatics toolkit
F Gabler, SZ Nam, S Till, M Mirdita, M Steinegger, J Söding, AN Lupas, ...
Current Protocols in Bioinformatics 72 (1), e108, 2020
382020
MMseqs2 desktop and local web server app for fast, interactive sequence searches
M Mirdita, M Steinegger, J Söding
Bioinformatics 35 (16), 2856–2858, 2019
252019
Cloud prediction of protein structure and function with PredictProtein for Debian
L Kaján, G Yachdav, E Vicedo, M Steinegger, M Mirdita, C Angermüller, ...
BioMed Research International 2013, 2013
232013
HFSP: high speed homology-driven function annotation of proteins
Y Mahlich, M Steinegger, B Rost, Y Bromberg
Bioinformatics 34 (13), i304-i312, 2018
142018
Fast and sensitive taxonomic assignment to metagenomic contigs
M Mirdita, M Steinegger, F Breitwieser, J Söding, E Levy Karin
Bioinformatics, 2021
62021
DescribePROT: database of amino acid-level protein structure and function predictions
B Zhao, A Katuwawala, CJ Oldfield, AK Dunker, E Faraggi, J Gsponer, ...
Nucleic Acids Research 49 (D1), D298-D308, 2021
42021
PredictProtein - Predicting Protein Structure and Function for 29 Years
M Bernhofer, C Dallago, T Karl, V Satagopam, M Heinzinger, M Littmann, ...
Nucleic Acids Research, 2021
32021
Highly multiplexed oligonucleotide probe-ligation testing enables efficient extraction-free SARS-CoV-2 detection and viral genotyping
JJ Credle, ML Robinson, J Gunn, D Monaco, B Sie, A Tchir, J Hardick, ...
Modern Pathology, 1-11, 2021
32021
Unifying the global coding sequence space enables the study of genes with unknown function across biomes
C Vanni, MS Schechter, SG Acinas, A Barberán, PL Buttigieg, ...
Cold Spring Harbor Laboratory, 2020
3*2020
Highly accurate protein structure prediction with AlphaFold
J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ...
Nature, 2021
22021
Going to extremes – a metagenomic journey into the dark matter of life
A Aevarsson, AK Kaczorowska, TB Adalsteinsson, J Ahlqvist, ...
FEMS Microbiology Letters, 2021
22021
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Articles 1–20