The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Combining local-structure, fold-recognition, and new fold methods for protein structure prediction
Abstract
This article presents an overview of the SAM-T02 method for protein fold recognition and the UNDERTAKER program for ab initio predictions. The SAM-T02 server is an automatic method that uses two-track hidden Markov models (HMMS) to find and align template proteins from PDB to the target protein. The two-track HMMs use an amino acid alphabet and one of several different local structure alphabets. The UNDERTAKER program is a new fragment-packing program that can use short or long fragments and alignments to create protein conformations. The HMMs and fold-recognition alignments from the SAM-T02 method were used to generate the fragment and alignment libraries used by UNDERTAKER. We present results on a few selected targets for which this combined method worked particularly well: T0129, T0181, T0135, T0130, and T0139.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Kabsch, W., & Sander, C. (1983) · Biopolymers · doi:10.1002/bip.360221211 · Cited by 15,320
Cited by
Comparative protein structure modeling using MODELLER
Webb, B., & Sali, A. (2016) · Current Protocols in Protein Science · doi:10.1002/cpps.20 · Cited by 730
“…tables dependent on structural features such as solvent exposure, secondary structure type, and hydrogen-bonding properties (Shi et al., 2001; Karchin et al., 2003; McGuffin and Jones, 2003; Zhou and Zhou, 2005) or on statistical potentials for residue interactions implied by the alignment…”
BackgroundMethodPhylogenomic analysis of the GIY-YIG nuclease superfamily
Dunin-Horkawicz, S., Feder, M., & Bujnicki, J. M. (2006) · BMC Genomics · doi:10.1186/1471-2164-7-98 · Cited by 133
Hawtin, S. R., Wesley, V. J., Simms, J., Argent, C. C. H., Latif, K., & Wheatley, M. (2005) · Molecular Endocrinology · doi:10.1210/me.2005-0148 · Cited by 24
Senet, P., Guzzo, A., Delarue, P., Laforge, C., Maisuradze, G. G., Heydel, J.-M., Neiers, F., & Nicolaï, A. (2026) · Chemical Science · doi:10.1039/d5sc06411b · Cited by 3
Metadata
- Authors
- Karplus, K., Karchin, R., Draper, J., Casper, J., Mandel-Gutfreund, Y., Diekhans, M., & Hughey, R.
- Venue
- Proteins: Structure, Function, and Genetics
- Publisher
- Wiley
- Published
- 2003
- Volume
- 53
- Issue
- S6
- Pages
- 491-496
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2106066024
- Cited by
- 294
- References
- 1
- FWCI
- 8.15
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.