The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Protein secondary structure prediction based on position-specific scoring matrices 1 1Edited by G. Von Heijne
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
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
Altschul, S. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.17.3389 · Cited by 73,302
Learning representations by back-propagating errors
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986) · Nature · doi:10.1038/323533a0 · Cited by 31,892
Kabsch, W., & Sander, C. (1983) · Biopolymers · doi:10.1002/bip.360221211 · Cited by 15,320
Chou, P. Y., & Fasman, G. D. (1974) · Biochemistry · doi:10.1021/bi00699a001 · Cited by 2,172
A new approach to protein fold recognition
Jones, D. T., Taylort, W. R., & Thornton, J. M. (1992) · Nature · doi:10.1038/358086a0 · Cited by 1,221
Self-citation
Cited by
The Phyre2 web portal for protein modeling, prediction and analysis
Kelley, L. A., Mezulis, S., Yates, C. M., Wass, M. N., & Sternberg, M. J. E. (2015) · Nature Protocols · doi:10.1038/nprot.2015.053 · Cited by 9,652
A Completely Reimplemented MPI Bioinformatics Toolkit with a New HHpred Server at its Core
Zimmermann, L., Stephens, A., Nam, S.-Z., Rau, D., Kübler, J., Lozajic, M., Gabler, F., Söding, J., Lupas, A. N., & Alva, V. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2017.12.007 · Cited by 2,522
Opportunities and obstacles for deep learning in biology and medicine
Ching, T., Himmelstein, D. S., Beaulieu-Jones, B. K., Kalinin, A. A., Do, B. T., Way, G. P., Ferrero, E., Agapow, P.-M., Zietz, M., Hoffman, M. M., et al. (2018) · Journal of The Royal Society Interface · doi:10.1098/rsif.2017.0387 · Cited by 2,310
HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
Remmert, M., Biegert, A., Hauser, A., & Söding, J. (2012) · Nature Methods · doi:10.1038/nmeth.1818 · Cited by 2,288
A tissue-specific atlas of mouse protein phosphorylation and expression
Huttlin, E. L., Jedrychowski, M. P., Elias, J. E., Goswami, T., Rad, R., Beausoleil, S. A., Villén, J., Haas, W., Sowa, M. E., & Gygi, S. P. (2010) · Cell · doi:10.1016/j.cell.2010.12.001 · Cited by 1,778
Showing your ID: intrinsic disorder as an ID for recognition, regulation and cell signaling
Uversky, V. N., Oldfield, C. J., & Dunker, A. K. (2005) · Journal of Molecular Recognition · doi:10.1002/jmr.747 · Cited by 847
Protein Sequence Analysis Using the MPI Bioinformatics Toolkit
Gabler, F., Nam, S., Till, S., Mirdita, M., Steinegger, M., Söding, J., Lupas, A. N., & Alva, V. (2020) · Current Protocols in Bioinformatics · doi:10.1002/cpbi.108 · Cited by 831
Advances in protein structure prediction and design
Kuhlman, B., & Bradley, P. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0163-x · Cited by 806
Intrinsic Disorder in Transcription Factors
Liu, J., Perumal, N. B., Oldfield, C. J., Su, E. W., Uversky, V. N., & Dunker, A. K. (2006) · Biochemistry · doi:10.1021/bi0602718 · Cited by 792
Deeley, R. G., Westlake, C., & Cole, S. P. C. (2006) · Physiological Reviews · doi:10.1152/physrev.00035.2005 · Cited by 761
D2P2: database of disordered protein predictions
Oates, M. E., Romero, P., Ishida, T., Ghalwash, M., Mizianty, M. J., Xue, B., Dosztányi, Z., Uversky, V. N., Obradovic, Z., Kurgan, L., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1226 · Cited by 705
Calorie restriction and SIRT3 trigger global reprogramming of the mitochondrial protein acetylome
Hebert, A. S., Dittenhafer-Reed, K. E., Yu, W., Bailey, D. J., Selen, E. S., Boersma, M. D., Carson, J. J., Tonelli, M., Balloon, A. J., Higbee, A. J., et al. (2013) · Molecular Cell · doi:10.1016/j.molcel.2012.10.024 · Cited by 636
Widespread protein aggregation as an inherent part of aging in C. elegans
David, D. C., Ollikainen, N., Trinidad, J. C., Cary, M. P., Burlingame, A. L., & Kenyon, C. (2010) · PLoS Biology · doi:10.1371/journal.pbio.1000450 · Cited by 627
Modeling the language of life – Deep Learning Protein Sequences
Heinzinger, M., Elnaggar, A., Wang, Y., Dallago, C., Nechaev, D., Matthes, F., & Rost, B. (2019) · doi:10.1101/614313 · Cited by 606
Modeling aspects of the language of life through transfer-learning protein sequences
Heinzinger, M., Elnaggar, A., Wang, Y., Dallago, C., Nechaev, D., Matthes, F., & Rost, B. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-3220-8 · Cited by 606
Genome-wide analysis of core cell cycle genes in Arabidopsis
Vandepoele, K., Raes, J., De Veylder, L., Rouzé, P., Rombauts, S., & Inzé, D. (2002) · The Plant Cell · doi:10.1105/tpc.010445 · Cited by 594
Global analysis of protein folding using massively parallel design, synthesis, and testing
Rocklin, G. J., Chidyausiku, T. M., Goreshnik, I., Ford, A., Houliston, S., Lemak, A., Carter, L., Ravichandran, R., Mulligan, V. K., Chevalier, A., et al. (2017) · Science · doi:10.1126/science.aan0693 · Cited by 501
Comparing two K-category assignments by a K-category correlation coefficient
Gorodkin, J. (2004) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2004.09.006 · Cited by 545
The architecture of respiratory supercomplexes
Letts, J. A., Fiedorczuk, K., & Sazanov, L. A. (2016) · Nature · doi:10.1038/nature19774 · Cited by 490
Rives, A., Meier, J., Sercu, T., Goyal, S., Lin, Z., Liu, J., Guo, D., Ott, M., Zitnick, C. L., Ma, J., et al. (2019) · doi:10.1101/622803 · Cited by 3,280
“…we compare to (1) one-hot amino acid representations, which results in the prior that predicts the most likely label for each position’s amino acid, and (2) representations from family-level frequencies summarized in position-specific scoring matrices (“PSSM”s; Jones, 1999) for each protein.”
MethodProikas-Cezanne, T., Waddell, S., Gaugel, A., Frickey, T., Lupas, A., & Nordheim, A. (2004) · Oncogene · doi:10.1038/sj.onc.1208331 · Cited by 332
Niwa, T., Ying, B.-W., Saito, K., Jin, W., Takada, S., Ueda, T., & Taguchi, H. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811922106 · Cited by 321
The protein structure prediction problem could be solved using the current PDB library
Zhang, Y., & Skolnick, J. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0407152101 · Cited by 297
Minezaki, Y., Homma, K., Kinjo, A. R., & Nishikawa, K. (2006) · Journal of Molecular Biology · doi:10.1016/j.jmb.2006.04.016 · Cited by 297
Progress in Modeling of Protein Structures and Interactions.
Schueler-Furman, O., Wang, C., Bradley, P., Misura, K., & Baker, D. (2005) · Science · doi:10.1126/science.1112160 · Cited by 294
Hallucinating symmetric protein assemblies
Wicky, B. I. M., Milles, L. F., Courbet, A., Ragotte, R. J., Dauparas, J., Kinfu, E., Tipps, S., Kibler, R. D., Baek, M., DiMaio, F., et al. (2022) · Science · doi:10.1126/science.add1964 · Cited by 240
Deep‐learning contact‐map guided protein structure prediction in CASP13
Zheng, W., Li, Y., Zhang, C., Pearce, R., Mortuza, S. M., & Zhang, Y. (2019) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.25792 · Cited by 208
Multiple sequence alignment modeling: Methods and applications
Chatzou, M., Magis, C., Chang, J.-M., Kemena, C., Bussotti, G., Erb, I., & Notredame, C. (2016) · Briefings in Bioinformatics · doi:10.1093/bib/bbv099 · Cited by 229
Structural basis for TetM-mediated tetracycline resistance
Dönhöfer, A., Franckenberg, S., Wickles, S., Berninghausen, O., Beckmann, R., & Wilson, D. N. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1208037109 · Cited by 217
Protein synthesis rates and ribosome occupancies reveal determinants of translation elongation rates
Riba, A., Di Nanni, N., Mittal, N., Arhné, E., Schmidt, A., & Zavolan, M. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1817299116 · Cited by 209
Mutations in the KIAA0196 Gene at the SPG8 Locus Cause Hereditary Spastic Paraplegia
Valdmanis, P. N., Meijer, I. A., Reynolds, A., Lei, A., MacLeod, P., Schlesinger, D., Zatz, M., Reid, E., Dion, P. A., Drapeau, P., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/510782 · Cited by 182
Protein sequence design with a learned potential
Anand, N., Eguchi, R., Mathews, I. I., Perez, C. P., Derry, A., Altman, R. B., & Huang, P.-S. (2022) · Nature Communications · doi:10.1038/s41467-022-28313-9 · Cited by 171
Greener, J. G., Kandathil, S. M., & Jones, D. T. (2019) · Nature Communications · doi:10.1038/s41467-019-11994-0 · Cited by 178
Self-citationNetCGlyc 1.0: Prediction of mammalian C-mannosylation sites
Julenius, K. (2007) · Glycobiology · doi:10.1093/glycob/cwm050 · Cited by 174
Protein-Protein Complex Structure Predictions by Multimeric Threading and Template Recombination
Mukherjee, S., & Zhang, Y. (2011) · Structure · doi:10.1016/j.str.2011.04.006 · Cited by 174
Noddings, C. M., Wang, R. Y.-R., & Agard, D. A. (2020) · doi:10.1101/2020.09.12.294975 · Cited by 166
Pandini, A., Denison, M. S., Song, Y., Soshilov, A. A., & Bonati, L. (2007) · Biochemistry · doi:10.1021/bi061460t · Cited by 160
Structure of Hsp90–p23–GR reveals the Hsp90 client-remodelling mechanism
Noddings, C. M., Wang, R. Y.-R., Johnson, J. L., & Agard, D. A. (2022) · Nature · doi:10.1038/s41586-021-04236-1 · Cited by 164
DISC1: Structure, Function, and Therapeutic Potential for Major Mental Illness
Soares, D. C., Carlyle, B. C., Bradshaw, N. J., & Porteous, D. J. (2011) · ACS Chemical Neuroscience · doi:10.1021/cn200062k · Cited by 129
Procko, E., Berguig, G. Y., Shen, B. W., Song, Y., Frayo, S., Convertine, A. J., Margineantu, D., Booth, G., Correia, B. E., Cheng, Y., et al. (2014) · Cell · doi:10.1016/j.cell.2014.04.034 · Cited by 127
The structure of human CST reveals a decameric assembly bound to telomeric DNA
Lim, C. J., Barbour, A. T., Zaug, A. J., Goodrich, K. J., McKay, A. E., Wuttke, D. S., & Cech, T. R. (2020) · Science · doi:10.1126/science.aaz9649 · Cited by 111
rawMSA: End-to-end Deep Learning using raw Multiple Sequence Alignments
Mirabello, C., & Wallner, B. (2019) · PLOS ONE · doi:10.1371/journal.pone.0220182 · Cited by 105
The human L-threonine 3-dehydrogenase gene is an expressed pseudogene
Edgar, A. J. (2002) · BMC Genetics · doi:10.1186/1471-2156-3-18 · Cited by 92
Aravind, L., & Koonin, E. V. (2000) · Genome Research · doi:10.1101/gr.10.8.1172 · Cited by 93
Structural and mechanistic basis of the EMC-dependent biogenesis of distinct transmembrane clients
Miller-Vedam, L. E., Bräuning, B., Popova, K. D., Schirle Oakdale, N. T., Bonnar, J. L., Prabu, J. R., Boydston, E. A., Sevillano, N., Shurtleff, M. J., Stroud, R. M., et al. (2020) · eLife · doi:10.7554/elife.62611 · Cited by 87
“…Quick2D, a tool within the Max-Plank Institute for Developmental Biology Bioinformatics Toolkit that visualizes several different secondary structure predictors (Jones, 1999; Cuff and Barton, 1999; Ouali and King, 2000; Rost, 2001; Lupas, 1991; Jones, 1994; Ward, 2004; Peng, 2006; Obradovic, 2005).”
MethodAn overview of the prediction of protein DNA-binding sites
Si, J., Zhao, R., & Wu, R. (2015) · International Journal of Molecular Sciences · doi:10.3390/ijms16035194 · Cited by 91
Structural insight into epitopes in the pregnancy-associated malaria protein VAR2CSA
Andersen, P., Nielsen, M. A., Resende, M., Rask, T. S., Dahlbäck, M., Theander, T., Lund, O., & Salanti, A. (2008) · PLoS Pathogens · doi:10.1371/journal.ppat.0040042 · Cited by 79
Mysling, S., Kristensen, K. K., Larsson, M., Kovrov, O., Bensadouen, A., Jørgensen, T. J., Olivecrona, G., Young, S. G., & Ploug, M. (2016) · eLife · doi:10.7554/elife.20958 · Cited by 77
Determining crystal structures through crowdsourcing and coursework
Horowitz, S., Koepnick, B., Martin, R., Tymieniecki, A., Winburn, A. A., Cooper, S., Flatten, J., Rogawski, D. S., Koropatkin, N. M., Hailu, T. T., et al. (2016) · Nature Communications · doi:10.1038/ncomms12549 · Cited by 75
A novel Cas family member, HEPL, regulates FAK and cell spreading
Singh, M. K., Dadke, D., Nicolas, E., Serebriiskii, I. G., Apostolou, S., Canutescu, A., Egleston, B. L., & Golemis, E. A. (2008) · Molecular Biology of the Cell · doi:10.1091/mbc.e07-09-0953 · Cited by 74
Singh, A. K., Bhattacharyya-Pakrasi, M., & Pakrasi, H. B. (2008) · Journal of Biological Chemistry · doi:10.1074/jbc.m800982200 · Cited by 73
Structure of the DASH/Dam1 complex shows its role at the yeast kinetochore-microtubule interface
Jenni, S., & Harrison, S. C. (2018) · Science · doi:10.1126/science.aar6436 · Cited by 72
BAP31: Physiological functions and roles in disease
Quistgaard, E. M. (2021) · Biochimie · doi:10.1016/j.biochi.2021.04.008 · Cited by 70
A cryo-ET survey of microtubules and intracellular compartments in mammalian axons
Foster, H. E., Ventura Santos, C., & Carter, A. P. (2022) · Journal of Cell Biology · doi:10.1083/jcb.202103154 · Cited by 69
M-TASSER: An Algorithm for Protein Quaternary Structure Prediction
Chen, H., & Skolnick, J. (2008) · Biophysical Journal · doi:10.1529/biophysj.107.114280 · Cited by 68
Guan, X., Madabushi, A., Chang, D.-Y., Fitzgerald, M. E., Shi, G., Drohat, A. C., & Lu, A.-L. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm678 · Cited by 65
AlphaDesign: A de novo protein design framework based on AlphaFold
Jendrusch, M., Korbel, J. O., & Sadiq, S. K. (2021) · doi:10.1101/2021.10.11.463937 · Cited by 65
Lipinski, K. A., Puchta, O., Surendranath, V., Kudla, M., & Golik, P. (2011) · Molecular Biology and Evolution · doi:10.1093/molbev/msr120 · Cited by 62
Vargas-Pinilla, P., Paixão-Côrtes, V. R., Paré, P., Tovo-Rodrigues, L., Vieira, C. M. D. A. G., Xavier, A., Comas, D., Pissinatti, A., Sinigaglia, M., Rigo, M. M., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1419399112 · Cited by 59
Critical Scaffolding Regions of the Tumor Suppressor Axin1 Are Natively Unfolded
Noutsou, M., Duarte, A. M. S., Anvarian, Z., Didenko, T., Minde, D. P., Kuper, I., de Ridder, I., Oikonomou, C., Friedler, A., Boelens, R., et al. (2011) · Journal of Molecular Biology · doi:10.1016/j.jmb.2010.11.013 · Cited by 58
Corrada, D., Soshilov, A. A., Denison, M. S., & Bonati, L. (2016) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004981 · Cited by 43
Structural Learning of Proteins Using Graph Convolutional Neural Networks
Zamora-Resendiz, R., & Crivelli, S. (2019) · doi:10.1101/610444 · Cited by 37
Mozaffari, M., Hoogeveen-Westerveld, M., Kwiatkowski, D., Sampson, J., Ekong, R., Povey, S., den Dunnen, J. T., van den Ouweland, A., Halley, D., & Nellist, M. (2009) · BMC Medical Genetics · doi:10.1186/1471-2350-10-88 · Cited by 36
The Charged Linker Modulates the Conformations and Molecular Interactions of Hsp90
López, A., Elimelech, A. R., Klimm, K., & Sattler, M. (2021) · ChemBioChem · doi:10.1002/cbic.202000699 · Cited by 30
Greener, J. G., & Jones, D. T. (2021) · PLOS ONE · doi:10.1371/journal.pone.0256990 · Cited by 29
Self-citationZech, R., Kiontke, S., Mueller, U., Oeckinghaus, A., & Kümmel, D. (2016) · Journal of Biological Chemistry · doi:10.1074/jbc.m116.732446 · Cited by 29
hu.MAP3.0: atlas of human protein complexes by integration of >25,000 proteomic experiments
Fischer, S. N., Claussen, E. R., Kourtis, S., Sdelci, S., Orchard, S., Hermjakob, H., Kustatscher, G., & Drew, K. (2025) · Molecular Systems Biology · doi:10.1038/s44320-025-00121-5 · Cited by 25
Crevenna, A. H., Madathil, S., Cohen, D. N., Wagenbach, M., Fahmy, K., & Howard, J. (2008) · Biophysical Journal · doi:10.1529/biophysj.108.132449 · Cited by 23
Corrada, D., Denison, M. S., & Bonati, L. (2017) · Molecular BioSystems · doi:10.1039/c7mb00005g · Cited by 24
Critical assessment of coiled-coil predictions based on protein structure data
Simm, D., Hatje, K., Waack, S., & Kollmar, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-91886-w · Cited by 24
FDXR variants cause adrenal insufficiency and atypical sexual development
Pignatti, E., Slone, J., Gómez Cano, M. Á., Campbell, T. M., Vu, J., Sauter, K.-S., Pandey, A. V., Martínez-Azorín, F., Alonso-Riaño, M., Neilson, D. E., et al. (2024) · JCI Insight · doi:10.1172/jci.insight.179071 · Cited by 12
Antimicrobial Activity of Cathelicidin-Derived Peptide from the Iberian Mole Talpa occidentalis
Otazo-Pérez, A., Asensio-Calavia, P., González-Acosta, S., Baca-González, V., López, M. R., Morales-delaNuez, A., & Pérez de la Lastra, J. M. (2022) · Vaccines · doi:10.3390/vaccines10071105 · Cited by 9
Refining the domain architecture model of the replication origin firing factor Treslin/TICRR
Ferreira, P., Sanchez-Pulido, L., Marko, A., Ponting, C. P., & Boos, D. (2022) · Life Science Alliance · doi:10.26508/lsa.202101088 · Cited by 9
Cardim-Pires, T. R., Sant’Anna, R., & Foguel, D. (2021) · Scientific Reports · doi:10.1038/s41598-021-02898-5 · Cited by 7
Computational generation of proteins with predetermined three-dimensional shapes using ProteinSolver
Strokach, A., Becerra, D., Corbi-Verge, C., Perez-Riba, A., & Kim, P. M. (2021) · STAR Protocols · doi:10.1016/j.xpro.2021.100505 · Cited by 6
Biophysical characterization of high-confidence, small human proteins
Whited, A. M., Jungreis, I., Allen, J., Cleveland, C. L., Mudge, J. M., Kellis, M., Rinn, J. L., & Hough, L. E. (2024) · Biophysical Reports · doi:10.1016/j.bpr.2024.100167 · Cited by 5
Lys716 in the transmembrane domain of yeast mitofusin Fzo1 modulates anchoring and fusion
Versini, R., Baaden, M., Cavellini, L., Cohen, M. M., Taly, A., & Fuchs, P. F. J. (2024) · Structure · doi:10.1016/j.str.2024.08.017 · Cited by 4
Lee, S. J., Joo, K., Sim, S., Lee, J., Lee, I.-H., & Lee, J. (2022) · Molecules · doi:10.3390/molecules27123711 · Cited by 3
Klimenko, V., Reiners, J., Applegate, V., Reimann, K., Hoeppner, A., Smits, S. H. J., & Nowack, E. C. M. (2025) · doi:10.1101/2025.01.15.633182
Metadata
- Authors
- Jones, D. T.
- Venue
- Journal of Molecular Biology
- Publisher
- Elsevier BV
- Published
- 1999-09
- Volume
- 292
- Issue
- 2
- Pages
- 195-202
- ISSN
- 0022-2836 (ISSN-L)
- OpenAlex
- W2153187042
- Cited by
- 5,449
- References
- 5
- Type
- book review
- 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.