Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes.

By Anders Krogh, B. Larsson, G. von Heijne, Erik L. L. Sonnhammer. 2001

12,728 citations recorded by the source corpus.

Subfields: Molecular Biology

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In Molecular Biology

1. Yang Zhang
2. David T. Jones
3. Burkhard Rost
4. Jinbo Xu
5. Arne Elofsson
6. Sheng Wang
7. Johannes Söding
8. Peer Bork

Citations in the corpus

• Multi-State Modeling of G-protein Coupled Receptors at Experimental Accuracy (2021, methodology): “Up to 100 residues towards N- and C-termini from the first and seventh TM helices were additionally considered for modeling not to lose any of their interactions with the TM domain and relevant TM helix residues because the annotations are based on a TMHMM prediction.(35)”
• The Pfam protein families database (2007, methodology): “These predictions are pre-computed over the sequence database by the following third party programs: TMHMM (10) (transmembrane regions), SignalP (11) (signal peptide regions), ncoils (12) (coiled-coil regions) and SEG (9) (low complexity regions).”
• The Pfam protein families database (2011, methodology): “These predictions are pre-computed over the sequence database by the following third party programs: TMHMM ( 10 ) (transmembrane regions), SignalP (11) (signal peptide regions), ncoils (12) (coiled-coil regions) and SEG (9) (low complexity regions).”
• Folding membrane proteins by deep transfer learning (2017, background): “It is estimated that 20-40% of all genes in most genomes encode MPs (Uhlén et al., 2015, Krogh et al., 2001) and larger genomes contain a higher fraction of MPs (Wallin and Heijne, 1998).”
• Multipass membrane protein structure prediction using Rosetta (2005, positive): “We used TMHMM, 31,32 TMPred, 33 MEMSAT2, 34 and HMMTOP 35,36 to define positions of N-and C-terminal residues of each of the TM helices in all TM proteins tested, which were used to approximate the membrane normal vector (see its definition in E env above) needed for our scoring function during each s”
• A highly conserved program of neuronal microexons is misregulated in autistic brains (2014, background): “, 2004); Transmembrane predictions, TMHMM (Krogh et al., 2001); ELM (Dinkel et al.”
• Archaeal Clusters of Orthologous Genes (arCOGs): An Update and Application for Analysis of Shared Features between Thermococcales, Methanococcales, and Methanobacteriales (2015, neutral): “0c program with default parameters [44].”
• InterPro: the protein sequence classification resource in 2025 (2024, neutral): “…about sequence features, including consensus annotations of long-range intrinsic disorder regions predicted by MobiDB-lite ( 15 ), and predictions of signal peptides, transmembrane regions and coiled-coils using the SignalP ( 16 ), Phobius ( 17 ), TMHMM ( 18 ) and Coils ( 19 ) software packages.”
• GPCR-I-TASSER: A hybrid approach to G protein-coupled receptor structure modeling and the application to the human genome (2015, methodology): “Here, C-score is defined as the product of the normalized Z-score from LOMETS threading and the cluster density from SPICKER, i.e.”
• Ecology of marine Bacteroidetes: a comparative genomics approach (2013, methodology): “, 2004) and TMHMM for transmembrane helix analysis (Krogh et al., 2001).”
• The Ensembl gene annotation system (2016, methodology): “We identify these signatures by both ab initio sequence search [SEG (95), SignalP (96), ncoils (97), TMHMM (98)] and searching protein domain databases for sequence matches [PRINTS (99), Pfscan (100), Pfam (101), TIGRFAM, SUPERFAMILY (102), SMART (103) and PIRSF (104)].”
• Prediction of lipoprotein signal peptides in Gram‐negative bacteria (2003, methodology): “N-terminal transmembrane helices N-terminal transmembrane helices are often mistaken as signal peptides, and vice versa (Krogh et al. 2001).”
• MycoCosm portal: gearing up for 1000 fungal genomes (2013, methodology): “SignalP (14) is used to detect the sequence motifs responsible for protein localization, TMHMM (15) identifies possible transmembrane domains and InterProScan (16) predicts functional domains from Pfam (17) and other databases.”
• Co-evolving residues in membrane proteins (2007, background): “The first examples of such compensatory changes were described by analyzing individual families having a solved structure (Altschuh et al., 1987, 1988).”