Browse by UCL people
Group by: Type | Date
Number of items: 66.
Article
Bertoni, Damian;
Tsenkov, Maxim;
Magana, Paulyna;
Nair, Sreenath;
Pidruchna, Ivanna;
Querino Lima Afonso, Marcelo;
Midlik, Adam;
... Velankar, Sameer; + view all
(2025)
AlphaFold Protein Structure Database 2025: a redesigned interface and updated structural coverage.
Nucleic Acids Research
, Article gkaf1226. 10.1093/nar/gkaf1226.
(In press).
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Buchan, Daniel WA;
Moffat, Lewis;
Lau, Andy;
Kandathil, Shaun M;
Jones, David T;
(2024)
Deep learning for the PSIPRED Protein Analysis Workbench.
Nucleic Acids Research
, 52
(W1)
W287-W293.
10.1093/nar/gkae328.
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Buchan, D;
Jones, DT;
(2019)
The PSIPRED Protein Analysis Workbench: 20 years on.
Nucleic Acids Research
, 47
(1)
pp. 402-407.
10.1093/nar/gkz297.
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Buchan, DW;
Jones, DT;
(2020)
Learning a Functional Grammar of Protein Domains using Natural Language Word Embedding Techniques.
Proteins
, 88
(4)
pp. 616-624.
10.1002/prot.25842.
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Buchan, DW;
Jones, DT;
(2017)
EigenTHREADER: Analogous protein fold recognition by efficient contact map threading.
Bioinformatics
, 33
(17)
pp. 2684-2690.
10.1093/bioinformatics/btx217.
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Buchan, DWA;
Jones, DT;
(2017)
Improved protein contact predictions with the MetaPSICOV2 server in CASP12.
Proteins: Structure, Function and Bioinformatics
10.1002/prot.25379.
(In press).
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Buchan, DWA;
Minneci, F;
Nugent, TCO;
Bryson, K;
Jones, DT;
(2013)
Scalable web services for the PSIPRED Protein Analysis Workbench.
Nucleic Acids Research
, 41
(W1)
W349-W357.
10.1093/nar/gkt381.
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Chandonia, J-M;
Adhikari, A;
Carraro, M;
Chhibber, A;
Cutting, GR;
Fu, Y;
Gasparini, A;
... Buckley, BA; + view all
(2017)
Lessons from the CAGI-4 Hopkins clinical panel challenge.
Human Mutation
, 38
(9)
pp. 1155-1168.
10.1002/humu.23225.
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Clark, WT;
Kasak, L;
Bakolitsa, C;
Hu, Z;
Andreoletti, G;
Babbi, G;
Bromberg, Y;
... LeBowitz, JH; + view all
(2019)
Assessment of predicted enzymatic activity of α‐N‐acetylglucosaminidase variants of unknown significance for CAGI 2016.
Human Mutation
, 40
(9)
pp. 1519-1529.
10.1002/humu.23875.
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Cozzetto, D;
Minneci, F;
Currant, H;
Jones, DT;
(2016)
FFPred 3: feature-based function prediction for all Gene Ontology domains.
Scientific Reports
, 6
, Article 31865. 10.1038/srep31865.
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Daneshjou, R;
Wang, Y;
Bromberg, Y;
Bovo, S;
Martelli, PL;
Babbi, G;
Di Lena, P;
... Morgan, AA; + view all
(2017)
Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges.
Human Mutation
, 38
(9)
pp. 1182-1192.
10.1002/humu.23280.
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Edwards, Y.J.K.;
Lobley, A.E.;
Pentony, M.M.;
Jones, D.T.;
(2009)
Insights into the regulation of intrinsically disordered proteins in the human proteome by analyzing sequence and gene expression data.
Genome Biology
, 10
(5)
, Article R50. 10.1186/gb-2009-10-5-r50.
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Edwards, YJK;
Bryson, K;
Jones, DT;
(2008)
A Meta-Analysis of Microarray Gene Expression in Mouse Stem Cells: Redefining Stemness.
PLOS ONE
, 3
(7)
, Article e2712. 10.1371/journal.pone.0002712.
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Edwards, YJK;
Lobley, AE;
Pentony, MM;
Jones, DT;
(2009)
Insights into the regulation of intrinsically disordered proteins in the human proteome by analyzing sequence and gene expression data.
Genome Biology
, 10
(5)
, Article R50. 10.1186/gb-2009-10-5-r50.
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Fa, R;
Cozzetto, D;
Wan, C;
Jones, D;
(2018)
Predicting human protein function with multi-task deep neural networks.
PLoS ONE
, 13
(6)
, Article e0198216. 10.1371/journal.pone.0198216.
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Giollo, M;
Jones, DT;
Carraro, M;
Leonardi, E;
Ferrari, C;
Tosatto, SC;
(2017)
Crohn Disease Risk Prediction-Best Practices and Pitfalls with Exome Data.
Human Mutation
, 38
(9)
pp. 1193-1200.
10.1002/humu.23177.
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Greener, JG;
Jones, DT;
(2021)
Differentiable molecular simulation can learn all the parameters in a coarse-grained force field for proteins.
PLOS ONE
, 16
(9)
, Article e0256990. 10.1371/journal.pone.0256990.
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Greener, JG;
Kandathil, SM;
Moffat, L;
Jones, DT;
(2022)
A guide to machine learning for biologists.
Nature Reviews Molecular Cell Biology
, 23
pp. 40-55.
10.1038/s41580-021-00407-0.
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Greener, JG;
Kandathil, SM;
Jones, DT;
(2019)
Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints.
Nature Communications
, 10
, Article 3977. 10.1038/s41467-019-11994-0.
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Greener, JG;
Moffat, L;
Jones, DT;
(2018)
Design of metalloproteins and novel protein folds using variational autoencoders.
Scientific Reports
, 8
, Article 16189. 10.1038/s41598-018-34533-1.
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Jain, Shantanu;
Bakolitsa, Constantina;
Brenner, Steven E;
Radivojac, Predrag;
Moult, John;
Repo, Susanna;
Hoskins, Roger A;
... The Critical Assessment of Genome Interpretation Consortium; + view all
(2024)
CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods.
Genome Biology
, 25
, Article 53. 10.1186/s13059-023-03113-6.
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Jiang, Y;
Oron, TR;
Clark, WT;
Bankapur, AR;
D'Andrea, D;
Lepore, R;
Funk, CS;
... Radivojac, P; + view all
(2016)
An expanded evaluation of protein function prediction methods shows an improvement in accuracy.
Genome Biology
, 17
, Article 184. 10.1186/s13059-016-1037-6.
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Jones, DT;
Thornton, JM;
(2022)
The impact of AlphaFold2 one year on.
Nature Methods
, 19
(1)
pp. 15-20.
10.1038/s41592-021-01365-3.
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Jones, D;
Wan, C;
(2020)
Protein function prediction is improved by creating synthetic feature samples with generative adversarial networks.
Nature Machine Intelligence
, 2
pp. 540-550.
10.1038/s42256-020-0222-1.
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Jones, DT;
Cozzetto, D;
(2014)
DISOPRED3: Precise disordered region predictions with annotated protein binding activity.
Bioinformatics
, 31
(6)
10.1093/bioinformatics/btu744.
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Jones, DT;
Kandathil, SM;
(2018)
High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features.
Bioinformatics
, 34
(19)
pp. 3308-3315.
10.1093/bioinformatics/bty341.
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Jones, DT;
Singh, T;
Kosciolek, T;
Tetchner, S;
(2014)
MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins.
Bioinformatics
10.1093/bioinformatics/btu791.
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Kandathil, Shaun M;
Lau, Andy M;
Jones, David T;
(2023)
Machine learning methods for predicting protein structure from single sequences.
Current Opinion in Structural Biology
, 81
, Article 102627. 10.1016/j.sbi.2023.102627.
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Kandathil, SM;
Greener, JG;
Lau, AM;
Jones, DT;
(2022)
Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterized proteins.
Proceedings of the National Academy of Sciences of the United States of America
, 119
(4)
, Article e2113348119. 10.1073/pnas.2113348119.
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Kandathil, S;
Greener, J;
Jones, DT;
(2019)
Prediction of inter-residue contacts with DeepMetaPSICOV in CASP13.
Proteins
, 87
(12)
pp. 1092-1099.
10.1002/prot.25779.
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Kandathil, SM;
Greener, JG;
Jones, DT;
(2019)
Recent Developments in Deep Learning Applied to Protein Structure Prediction.
Proteins
10.1002/prot.25824.
(In press).
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Kosciolek, T;
Buchan, DWA;
Jones, DTJ;
(2017)
Predictions of backbone dynamics in Intrinsically disordered proteins using de novo fragment-based protein structure predictions.
Scientific Reports
, 6
, Article 6999. 10.1038/s41598-017-07156-1.
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Kosciolek, T;
Jones, DT;
(2016)
Accurate contact predictions using covariation techniques and machine learning.
Proteins
, 84
(S1)
pp. 145-151.
10.1002/prot.24863.
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Kosciolek, T;
Jones, DT;
(2014)
De novo structure prediction of globular proteins aided by sequence variation-derived contacts.
PLoS One
, 9
(3)
, Article e92197 . 10.1371/journal.pone.0092197.
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Koussounadis, A;
Redfern, OC;
Jones, DT;
(2009)
Improving classification in protein structure databases using text mining.
BMC BIOINFORMATICS
, 10
, Article 129. 10.1186/1471-2105-10-129.
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Kryshtafovych, A;
Moult, J;
Billings, WM;
Della Corte, D;
Fidelis, K;
Kwon, S;
Olechnovič, K;
... CASP-COVID participants; + view all
(2021)
Modeling SARS-CoV-2 proteins in the CASP-commons experiment.
Proteins
, 89
(12)
pp. 1987-1996.
10.1002/prot.26231.
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Lewis, TE;
Sillitoe, I;
Andreeva, A;
Blundell, TL;
Buchan, DW;
Chothia, C;
Cozzetto, D;
... Orengo, C; + view all
(2014)
Genome3D: exploiting structure to help users understand their sequences.
Nucleic Acids Research
, 43
(D1)
D382-D386.
10.1093/nar/gku973.
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Lewis, TE;
Sillitoe, I;
Andreeva, A;
Blundell, TL;
Buchan, DW;
Chothia, C;
Cuff, A;
... Orengo, C; + view all
(2013)
Genome3D: a UK collaborative project to annotate genomic sequences with predicted 3D structures based on SCOP and CATH domains.
Nucleic Acids Research
, 41
(Databa)
D499 - D507.
10.1093/nar/gks1266.
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Lise, S;
Archambeau, C;
Pontil, M;
Jones, DT;
(2009)
Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods.
BMC Bioinformatics
, 10
, Article 365. 10.1186/1471-2105-10-365.
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Lise, S;
Buchan, D;
Pontil, M;
Jones, DT;
(2011)
Predictions of Hot Spot Residues at Protein-Protein Interfaces Using Support Vector Machines.
PLOS ONE
, 6
(2)
, Article e16774. 10.1371/journal.pone.0016774.
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Lise, S;
Walker-Taylor, A;
Jones, DT;
(2006)
Docking protein domains in contact space.
BMC BIOINFORMATICS
, 7
, Article 310. 10.1186/1471-2105-7-310.
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Lobley, A;
Swindells, MB;
Orengo, CA;
Jones, DT;
(2007)
Inferring function using patterns of native disorder in proteins.
PLOS COMPUT BIOL
, 3
(8)
, Article e162. 10.1371/journal.pcbi.0030162.
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McGuffin, L.J.;
Smith, R.T.;
Bryson, K.;
Sørensen, S.-A.;
Jones, D.T.;
(2006)
High throughput profile-profile based fold recognition for the entire human proteome.
BMC Bioinformatics
, 7
(1)
p. 288.
10.1186/1471-2105-7-288.
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Minneci, F;
Piovesan, D;
Cozzetto, D;
Jones, DT;
(2013)
FFPred 2.0: Improved Homology-Independent Prediction of Gene Ontology Terms for Eukaryotic Protein Sequences.
PLoS One
, 8
(5)
, Article e63754. 10.1371/journal.pone.0063754.
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Moffat, L;
Jones, DT;
(2021)
Increasing the Accuracy of Single Sequence Prediction Methods Using a Deep Semi-Supervised Learning Framework.
Bioinformatics
10.1093/bioinformatics/btab491.
(In press).
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Necci, M;
Piovesan, D;
CAID Predictors, .;
DisProt Curators, .;
Tosatto, SCE;
(2021)
Critical assessment of protein intrinsic disorder prediction.
Nature Methods
, 18
(5)
pp. 472-481.
10.1038/s41592-021-01117-3.
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Nugent, T;
Cozzetto, D;
Jones, DT;
(2013)
Evaluation of predictions in the CASP10 model refinement category.
Proteins
, 82
(Issue )
pp. 98-111.
10.1002/prot.24377.
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Nugent, T;
Jones, DT;
(2013)
Membrane protein orientation and refinement using a knowledge-based statistical potential.
BMC Bioinformatics
, 14
(Septem)
, Article 276. 10.1186/1471-2105-14-276.
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Nugent, T;
Jones, DT;
(2010)
Predicting Transmembrane Helix Packing Arrangements using Residue Contacts and a Force-Directed Algorithm.
PLoS Computational Biology
, 6
(3)
, Article e1000714. 10.1371/journal.pcbi.1000714.
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Nugent, T;
Jones, DT;
(2009)
Transmembrane protein topology prediction using support vector machines.
BMC BIOINFORMATICS
, 10
, Article 159. 10.1186/1471-2105-10-159.
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Radivojac, P;
Clark, WT;
Oron, TR;
Schnoes, AM;
Wittkop, T;
Sokolov, A;
Graim, K;
... Friedberg, I; + view all
(2013)
A large-scale evaluation of computational protein function prediction.
Nature Methods
, 10
(3)
pp. 221-227.
10.1038/NMETH.2340.
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Rafi, AM;
Nogina, D;
Penzar, D;
Lee, D;
Lee, D;
Kim, N;
Kim, S;
... Random Promoter DREAM Challenge Consortium; + view all
(2024)
A community effort to optimize sequence-based deep learning models of gene regulation.
Nature Biotechnology
10.1038/s41587-024-02414-w.
(In press).
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Sadowski, M.I.;
Jones, D.T.;
(2009)
An automatic method for assessing structural importance of amino acid positions.
BMC Structural Biology
, 9
, Article 10. 10.1186/1472-6807-9-10.
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Senior, A;
Evans, R;
Jumper, J;
Kirkpatrick, J;
Sifre, L;
Green, T;
Qin, C;
... Hassabis, D; + view all
(2020)
Improved protein structure prediction using potentials from deep learning.
Nature
, 577
pp. 706-710.
10.1038/s41586-019-1923-7.
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Senior, AW;
Evans, R;
Jumper, J;
Kirkpatrick, J;
Sifre, L;
Green, T;
Qin, C;
... Hassabis, D; + view all
(2019)
Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13).
Proteins
, 87
(12)
pp. 1141-1148.
10.1002/prot.25834.
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Sillitoe, I;
Andreeva, A;
Blundell, TL;
Buchan, DWA;
Finn, RD;
Gough, J;
Jones, D;
... Orengo, C; + view all
(2019)
Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation.
Nucleic Acids Research
10.1093/nar/gkz967.
(In press).
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Tan, CW;
Jones, DT;
(2008)
Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction.
BMC BIOINFORMATICS
, 9
, Article 94. 10.1186/1471-2105-9-94.
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Thomas, S;
Mohammed, F;
Reijmers, RM;
Woolston, A;
Stauss, T;
Kennedy, A;
Stirling, D;
... Stauss, HJ; + view all
(2019)
Framework engineering to produce dominant T cell receptors with enhanced antigen-specific function.
Nature Communications
, 10
(1)
, Article 4451. 10.1038/s41467-019-12441-w.
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Wan, C;
Cozzetto, D;
Fa, R;
Jones, DT;
(2019)
Using deep maxout neural networks to improve the accuracy of function prediction from protein interaction networks.
PLoS One
, 14
(7)
, Article e0209958. 10.1371/journal.pone.0209958.
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Wan, C;
Lees, JG;
Minneci, F;
Orengo, CA;
Jones, DT;
(2017)
Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster.
PLoS Computational Biology
, 13
(10)
, Article e1005791. 10.1371/journal.pcbi.1005791.
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Welby, E;
Lakowski, J;
Di Foggia, V;
Budinger, D;
Gonzalez-Cordero, A;
Lun, ATL;
Epstein, M;
... Sowden, JC; + view all
(2017)
Isolation and Comparative Transcriptome Analysis of Human Fetal and iPSC-Derived Cone Photoreceptor Cells.
Stem Cell Reports
, 9
(6)
pp. 1898-1915.
10.1016/j.stemcr.2017.10.018.
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Xu, Q;
Tang, Q;
Katsonis, P;
Lichtarge, O;
Jones, D;
Bovo, S;
Babbi, G;
... Dunbrack, RL; + view all
(2017)
Benchmarking predictions of allostery in liver pyruvate kinase in CAGI4.
Human Mutation
, 38
(9)
pp. 1123-1131.
10.1002/humu.23222.
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Zhou, N;
Jiang, Y;
Bergquist, TR;
Lee, AJ;
Kacsoh, BZ;
Crocker, AW;
Lewis, KA;
... Friedberg, I; + view all
(2019)
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens.
Genome Biology
, 20
(1)
, Article 244. 10.1186/s13059-019-1835-8.
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Book chapter
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Corney, D.;
Byrne, E.;
Buxton, B.;
Jones, D.;
(2008)
A logical framework for template creation and information extraction.
In: Lin, T.Y. and Xie, Y. and Wasilewska, A. and Liau, C.-J., (eds.)
Data Mining: Foundations and Practice.
(pp. 79-108).
Springer Verlag: Berlin/ Heidelberg, Germany.
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Cozzetto, D;
Jones, DT;
(2016)
Computational Methods for Annotation Transfers from Sequence.
In: Dessimoz, C and Škunca, N, (eds.)
The Gene Ontology Handbook: Part II.
(pp. 55-67).
Springer New York: New York, USA.
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Working / discussion paper
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The CAFA Consortium;
Jones, D;
Wan, C;
Cozzetto, D;
Fa, R;
(2019)
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens.
Cold Spring Harbor Laboratory Press
(In press).
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