ProfessorMichaelSternberg

Todd S, Todd P, Fol Leymarie F, Latham W, Kelley LA, Sternberg M, Hugues J, Taylor Set al., 2015, FoldSynth: Interactive 2D/3D visualisation platform for molecular strands, Pages: 41-50

FoldSynth is an interactive platform designed to help understand the characteristics and commonly used visual abstractions of molecular strands with an emphasis on proteins and DNA. It uses a simple model of molecular forces to give real time interactive animations of the folding and docking processes. The shape of a molecular strand is shown as a 3D visualisation floating above a 2D triangular matrix representing distance constraints, contact maps or other features of residue pairs. As well as more conventional raster plots, contact maps can be shown with vectors representing the grouping of contacts as secondary structures. The 2D visualisation is also interactive and can be used to manipulate a molecule, define constraints, control and view the folding dynamically, or even design new molecules. While the 3D visualisation is more realistic showing a molecule representation approximating the physical behavior and spatial properties, the 2D visualisation offers greater visibility, in that all molecular positions (and pairings) are always in view; the 3D mode may suffer occlusions and create complex views which are typically hard to understand to humans.

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• Citations: 2

Di Fruscia P, Zacharioudakis E, Liu C, Moniot S, Laohasinnarong S, Khongkow M, Harrison IF, Koltsida K, Reynolds CR, Schmidtkunz K, Jung M, Chapman KL, Steegborn C, Dexter DT, Sternberg MJE, Lam EW-F, Fuchter MJet al., 2015, The Discovery of a Highly Selective 5,6,7,8-Tetrahydrobenzo[4,5]thieno[ 2,3-<i>d</i>] pyrimidin-4(3<i>H</i>)-one SIRT2 Inhibitor that is Neuroprotective in an in vitro Parkinson's Disease Model, CHEMMEDCHEM, Vol: 10, Pages: 69-82, ISSN: 1860-7179

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• Citations: 58

Irimia M, Weatheritt RJ, Ellis JD, Parikshak NN, Gonatopoulos-Pournatzis T, Babor M, Quesnel-Vallieres M, Tapial J, Raj B, O'Hanlon D, Barrios-Rodiles M, Sternberg MJE, Cordes SP, Roth FP, Wrana JL, Geschwind DH, Blencowe BJet al., 2014, A Highly Conserved Program of Neuronal Microexons Is Misregulated in Autistic Brains, Cell, Vol: 159, Pages: 1511-1523, ISSN: 0092-8674

Alternative splicing (AS) generates vast transcriptomicand proteomic complexity. However, whichof the myriad of detected AS events provide importantbiological functions is not well understood.Here, we define the largest program of functionallycoordinated, neural-regulated AS described to datein mammals. Relative to all other types of AS withinthis program, 3-15 nucleotide ‘‘microexons’’ displaythe most striking evolutionary conservation andswitch-like regulation. These microexons modulatethe function of interaction domains of proteinsinvolved in neurogenesis. Most neural microexonsare regulated by the neuronal-specific splicing factornSR100/SRRM4, through its binding to adjacentintronic enhancer motifs. Neural microexons arefrequently misregulated in the brains of individualswith autism spectrum disorder, and this misregulationis associated with reduced levels of nSR100.The results thus reveal a highly conserved programof dynamic microexon regulation associated withthe remodeling of protein-interaction networks duringneurogenesis, the misregulation of which islinked to autism.

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Talman AM, Prieto JH, Marques S, Ubaida-Mohien C, Lawniczak M, Wass MN, Xu T, Frank R, Ecker A, Stanway RS, Krishna S, Sternberg MJE, Christophides GK, Graham DR, Dinglasan RR, Yates JR, Sinden REet al., 2014, Proteomic analysis of the <i>Plasmodium</i> male gamete reveals the key role for glycolysis in flagellar motility, MALARIA JOURNAL, Vol: 13

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• Citations: 37

Yates CM, Filippis I, Kelley LA, Sternberg MJEet al., 2014, SuSPect: enhanced prediction of single amino acid variant (SAV) phenotype using network features, Journal of Molecular Biology, Vol: 426, Pages: 2692-2701, ISSN: 0022-2836

Whole-genome and exome sequencing studies reveal many genetic variants between individuals, some of which are linked to disease. Many of these variants lead to single amino acid variants (SAVs), and accurate prediction of their phenotypic impact is important. Incorporating sequence conservation and network-level features, we have developed a method, SuSPect (Disease-Susceptibility-based SAV Phenotype Prediction), for predicting how likely SAVs are to be associated with disease. SuSPect performs significantly better than other available batch methods on the VariBench benchmarking dataset, with a balanced accuracy of 82%. SuSPect is available at www.sbg.bio.ic.ac.uk/suspect. The Web site has been implemented in Perl and SQLite and is compatible with modern browsers. An SQLite database of possible missense variants in the human proteome is available to download at www.sbg.bio.ic.ac.uk/suspect/download.html.

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Yates CM, Sternberg MJE, 2013, The Effects of Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) on Protein Protein Interactions, JOURNAL OF MOLECULAR BIOLOGY, Vol: 425, Pages: 3949-3963, ISSN: 0022-2836

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• Citations: 146

Alexov E, Sternberg M, 2013, Understanding Molecular Effects of Naturally Occurring Genetic Differences, JOURNAL OF MOLECULAR BIOLOGY, Vol: 425, Pages: 3911-3913, ISSN: 0022-2836

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• Citations: 15

Adzhubei AA, Sternberg MJE, Makarov AA, 2013, Polyproline-II Helix in Proteins: Structure and Function, JOURNAL OF MOLECULAR BIOLOGY, Vol: 425, Pages: 2100-2132, ISSN: 0022-2836

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• Citations: 363

Yates CM, Sternberg MJE, 2013, Proteins and Domains Vary in Their Tolerance of Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs), JOURNAL OF MOLECULAR BIOLOGY, Vol: 425, Pages: 1274-1286, ISSN: 0022-2836

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• Citations: 28

Bryant WA, Sternberg MJE, Pinney JW, 2013, AMBIENT: Active Modules for Bipartite Networks - using high-throughput transcriptomic data to dissect metabolic response, BMC SYSTEMS BIOLOGY, Vol: 7, ISSN: 1752-0509

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• Citations: 9

Radivojac P, Clark WT, Oron TR, Schnoes AM, Wittkop T, Sokolov A, Graim K, Funk C, Verspoor K, Ben-Hur A, Pandey G, Yunes JM, Talwalkar AS, Repo S, Souza ML, Piovesan D, Casadio R, Wang Z, Cheng J, Fang H, Goughl J, Koskinen P, Toronen P, Nokso-Koivisto J, Holm L, Cozzetto D, Buchan DWA, Bryson K, Jones DT, Limaye B, Inamdar H, Datta A, Manjari SK, Joshi R, Chitale M, Kihara D, Lisewski AM, Erdin S, Venner E, Lichtarge O, Rentzsch R, Yang H, Romero AE, Bhat P, Paccanaro A, Hamp T, Kassner R, Seemayer S, Vicedo E, Schaefer C, Achten D, Auer F, Boehm A, Braun T, Hecht M, Heron M, Hoenigschmid P, Hopf TA, Kaufmann S, Kiening M, Krompass D, Landerer C, Mahlich Y, Roos M, Bjorne J, Salakoski T, Wong A, Shatkay H, Gatzmann F, Sommer I, Wass MN, Sternberg MJE, Skunca N, Supek F, Bosnjak M, Panov P, Dzeroski S, Smuc T, Kourmpetis YAI, van Dijk ADJ, ter Braak CJF, Zhou Y, Gong Q, Dong X, Tian W, Falda M, Fontana P, Lavezzo E, Di Camillo B, Toppo S, Lan L, Djuric N, Guo Y, Vucetic S, Bairoch A, Linial M, Babbitt PC, Brenner SE, Orengo C, Rost B, Mooney SD, Friedberg Iet al., 2013, A large-scale evaluation of computational protein function prediction, NATURE METHODS, Vol: 10, Pages: 221-227, ISSN: 1548-7091

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• Citations: 578

Mao C, Shukla M, Larrouy-Maumus G, Dix FL, Kelley LA, Sternberg MJ, Sobral BW, de Carvalho LPSet al., 2013, Functional assignment of <i>Mycobacterium tuberculosis</i> proteome revealed by genome-scale fold-recognition, TUBERCULOSIS, Vol: 93, Pages: 40-46, ISSN: 1472-9792

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• Citations: 11

Janin J, Sternberg MJE, 2013, Protein flexibility, not disorder, is intrinsic to molecular recognition., F1000 Biol Rep, Vol: 5, ISSN: 1757-594X

An 'intrinsically disordered protein' (IDP) is assumed to be unfolded in the cell and perform its biological function in that state. We contend that most intrinsically disordered proteins are in fact proteins waiting for a partner (PWPs), parts of a multi-component complex that do not fold correctly in the absence of other components. Flexibility, not disorder, is an intrinsic property of proteins, exemplified by X-ray structures of many enzymes and protein-protein complexes. Disorder is often observed with purified proteins in vitro and sometimes also in crystals, where it is difficult to distinguish from flexibility. In the crowded environment of the cell, disorder is not compatible with the known mechanisms of protein-protein recognition, and, foremost, with its specificity. The self-assembly of multi-component complexes may, nevertheless, involve the specific recognition of nascent polypeptide chains that are incompletely folded, but then disorder is transient, and it must remain under the control of molecular chaperones and of the quality control apparatus that obviates the toxic effects it can have on the cell.

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Lewis TE, Sillitoe I, Andreeva A, Blundell TL, Buchan DW, Chothia C, Cuff A, Dana JM, Filippis I, Gough J, Hunter S, Jones DT, Kelley LA, Kleywegt GJ, Minneci F, Mitchell A, Murzin AG, Ochoa-Montano B, Rackham OJ, Smith J, Sternberg MJ, Velankar S, Yeats C, Orengo Cet al., 2013, Genome3D: a UK collaborative project to annotate genomic sequences with predicted 3D structures based on SCOP and CATH domains, Nucleic Acids Res, Vol: 41, Pages: D499-D507, ISSN: 1362-4962

Genome3D, available at http://www.genome3d.eu, is a new collaborative project that integrates UK-based structural resources to provide a unique perspective on sequence-structure-function relationships. Leading structure prediction resources (DomSerf, FUGUE, Gene3D, pDomTHREADER, Phyre and SUPERFAMILY) provide annotations for UniProt sequences to indicate the locations of structural domains (structural annotations) and their 3D structures (structural models). Structural annotations and 3D model predictions are currently available for three model genomes (Homo sapiens, E. coli and baker's yeast), and the project will extend to other genomes in the near future. As these resources exploit different strategies for predicting structures, the main aim of Genome3D is to enable comparisons between all the resources so that biologists can see where predictions agree and are therefore more trusted. Furthermore, as these methods differ in whether they build their predictions using CATH or SCOP, Genome3D also contains the first official mapping between these two databases. This has identified pairs of similar superfamilies from the two resources at various degrees of consensus (532 bronze pairs, 527 silver pairs and 370 gold pairs).

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Phan HTT, Stemberg MJE, Gelenbe E, 2012, Aligning protein-protein interaction networks using random neural networks, Pages: 167-172

We have developed RNNI, a global alignment method for protein-protein interaction networks between species, using a random neural network model (RNN) tailored for the alignment problem. The benchmark of the method in comparison with other available alignment approaches was performed using a range of measurements. The alignment results of the human and yeast pair showed that RNNI is capable of generating alignments with large conserved networks with functionally-related protein pairs while maintaining the closeness to the naive- sequence homology approach (BLAST). © 2012 IEEE.

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• Citations: 13

David A, Kelley LA, Sternberg MJE, 2012, A new structural model of the acid-labile subunit: pathogenetic mechanisms of short stature-causing mutations, JOURNAL OF MOLECULAR ENDOCRINOLOGY, Vol: 49, Pages: 213-220, ISSN: 0952-5041

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• Citations: 14

Sternberg MJE, Tamaddoni-Nezhad A, Lesk VI, Kay E, Hitchen PG, Cootes A, van Alphen LB, Lamoureux MP, Jarrelle HC, Rawlings CJ, Soo EC, Szymanski CM, Dell A, Wren BW, Muggleton SHet al., 2012, Gene Function Hypotheses for the Campylobacter jejuni Glycome Generated by a Logic-Based Approach, Journal of Molecular Biology, Vol: 425, Pages: 186-197, ISSN: 1089-8638

Increasingly, experimental data on biological systems are obtained from several sources and computational approaches are required to integrate this information and derive models for the function of the system. Here, we demonstrate the power of a logic-based machine learning approach to propose hypotheses for gene function integrating information from two diverse experimental approaches. Specifically, we use inductive logic programming that automatically proposes hypotheses explaining the empirical data with respect to logically encoded background knowledge. We study the capsular polysaccharide biosynthetic pathway of the major human gastrointestinal pathogen Campylobacter jejuni. We consider several key steps in the formation of capsular polysaccharide consisting of 15 genes of which 8 have assigned function, and we explore the extent to which functions can be hypothesised for the remaining 7. Two sources of experimental data provide the information for learning—the results of knockout experiments on the genes involved in capsule formation and the absence/presence of capsule genes in a multitude of strains of different serotypes. The machine learning uses the pathway structure as background knowledge. We propose assignments of specific genes to five previously unassigned reaction steps. For four of these steps, there was an unambiguous optimal assignment of gene to reaction, and to the fifth, there were three candidate genes. Several of these assignments were consistent with additional experimental results. We therefore show that the logic-based methodology provides a robust strategy to integrate results from different experimental approaches and propose hypotheses for the behaviour of a biological system.

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Lin D, Chen J, Watanabe H, Muggleton SH, Jain P, Sternberg MJE, Baxter C, Currie RA, Dunbar SJ, Earll M, Salazar JDet al., 2012, Does multi-clause learning help in real-world applications?, Pages: 221-237, ISSN: 0302-9743

The ILP system Progol is incomplete in not being able to generalise a single example to multiple clauses. This limitation is referred as single-clause learning (SCL) in this paper. However, according to the Blumer bound, incomplete learners such as Progol can have higher predictive accuracy while use less search than more complete learners. This issue is particularly relevant in real-world problems, in which it is unclear whether the unknown target theory or its approximation is within the hypothesis space of the incomplete learner. This paper uses two real-world applications in systems biology to study whether it is necessary to have complete multi-clause learning (MCL) methods, which is computationally expensive but capable of deriving multi-clause hypotheses that is in the systems level. The experimental results show that in both applications there do exist datasets, in which MCL has significantly higher predictive accuracies than SCL. On the other hand, MCL does not outperform SCL all the time due to the existence of the target hypothesis or its approximations within the hypothesis space of SCL. © 2012 Springer-Verlag Berlin Heidelberg.

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• Citations: 3

Wass MN, Stanway R, Blagborough AM, Lal K, Prieto JH, Raine D, Sternberg MJE, Talman AM, Tomley F, Yates J, Sinden REet al., 2012, Proteomic analysis of Plasmodium in the mosquito: progress and pitfalls, Parasitology, Vol: 139, Pages: 1131-1145, ISSN: 1469-8161

Here we discuss proteomic analyses of whole cell preparations of the mosquito stages of malaria parasite development (i.e.gametocytes, microgamete, ookinete, oocyst and sporozoite) of Plasmodium berghei. We also include critiques of theproteomes of two cell fractions from the purified ookinete, namely the micronemes and cell surface. Whereas we summarisekey biological interpretations of the data, we also try to identify key methodological constraints we have met, only some ofwhich we were able to resolve. Recognising the need to translate the potential of current genome sequencing into functionalunderstanding, we report our efforts to develop more powerful combinations of methods for the in silico prediction ofprotein function and location. We have applied this analysis to the proteome of the male gamete, a cell whose very simplestructural organisation facilitated interpretation of data. Some of the in silico predictions made have now been supported byongoing protein tagging and genetic knockout studies. We hope this discussion may assist future studies.

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Santos JCA, Nassif H, Page D, Muggleton SH, Sternberg MJEet al., 2012, Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study, BMC BIOINFORMATICS, Vol: 13, ISSN: 1471-2105

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• Citations: 16

Wass MN, Barton G, Sternberg MJE, 2012, CombFunc: predicting protein function using heterogeneous data sources, NUCLEIC ACIDS RESEARCH, Vol: 40, Pages: W466-W470, ISSN: 0305-1048

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• Citations: 44

Reynolds CR, Amini AC, Muggleton SH, Sternberg MJEet al., 2012, Assessment of a Rule-Based Virtual Screening Technology (INDDEx) on a Benchmark Data Set, JOURNAL OF PHYSICAL CHEMISTRY B, Vol: 116, Pages: 6732-6739, ISSN: 1520-6106

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• Citations: 7

Phan HTT, Sternberg MJE, 2012, PINALOG: a novel approach to align protein interaction networks-implications for complex detection and function prediction, BIOINFORMATICS, Vol: 28, Pages: 1239-1245, ISSN: 1367-4803

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• Citations: 66

David A, Razali R, Wass MN, Sternberg MJEet al., 2012, Protein-Protein Interaction Sites are Hot Spots for Disease-Associated Nonsynonymous SNPs, HUMAN MUTATION, Vol: 33, Pages: 359-363, ISSN: 1059-7794

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• Citations: 110

Di Fruscia P, Ho K-K, Laohasinnarong S, Khonghow M, Kroll SHB, Islam SA, Sternberg MJE, Schmidtkunz K, Jung M, Lam EW-F, Fuchter MJet al., 2012, The discovery of novel 10,11-dihydro-5H-dibenz[b,f]azepine SIRT2 inhibitors, MedChemComm

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Chambers JC, Zhang W, Sehmi J, Li X, Wass MN, Van der Harst P, Holm H, Sanna S, Kavousi M, Baumeister SE, Coin LJ, Deng G, Gieger C, Heard-Costa NL, Hottenga J-J, Kuehnel B, Kumar V, Lagou V, Liang L, Luan J, Vidal PM, Leach IM, O'Reilly PF, Peden JF, Rahmioglu N, Soininen P, Speliotes EK, Yuan X, Thorleifsson G, Alizadeh BZ, Atwood LD, Borecki IB, Brown MJ, Charoen P, Cucca F, Das D, de Geus EJC, Dixon AL, Doering A, Ehret G, Eyjolfsson GI, Farrall M, Forouhi NG, Friedrich N, Goessling W, Gudbjartsson DF, Harris TB, Hartikainen A-L, Heath S, Hirschfield GM, Hofman A, Homuth G, Hyppoenen E, Janssen HLA, Johnson T, Kangas AJ, Kema IP, Kuehn JP, Lai S, Lathrop M, Lerch MM, Li Y, Liang TJ, Lin J-P, Loos RJF, Martin NG, Moffatt MF, Montgomery GW, Munroe PB, Musunuru K, Nakamura Y, O'Donnell CJ, Olafsson I, Penninx BW, Pouta A, Prins BP, Prokopenko I, Puls R, Ruokonen A, Savolainen MJ, Schlessinger D, Schouten JNL, Seedorf U, Sen-Chowdhry S, Siminovitch KA, Smit JH, Spector TD, Tan W, Teslovich TM, Tukiainen T, Uitterlinden AG, Van der Klauw MM, Vasan RS, Wallace C, Wallaschofski H, Wichmann H-E, Willemsen G, Wuertz P, Xu C, Yerges-Armstrong LM, Abecasis GR, Ahmadi KR, Boomsma DI, Caulfield M, Cookson WO, van Duijn CM, Froguel P, Matsuda K, McCarthy MI, Meisinger C, Mooser V, Pietilainen KH, Schumann G, Snieder H, Sternberg MJE, Stolk RP, Thomas HC, Thorsteinsdottir U, Uda M, Waeber G, Wareham NJ, Waterworth DM, Watkins H, Whitfield JB, Witteman JCM, Wolffenbuttel BHR, Fox CS, Ala-Korpela M, Stefansson K, Vollenweider P, Voelzke H, Schadt EE, Scott J, Jarvelin M-R, Elliott P, Kooner JSet al., 2011, Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma, NATURE GENETICS, Vol: 43, Pages: 1131-1138, ISSN: 1061-4036

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• Citations: 409

Ehret GB, Munroe PB, Rice KM, Bochud M, Johnson AD, Chasman DI, Smith AV, Tobin MD, Verwoert GC, Hwang S-J, Pihur V, Vollenweider P, O'Reilly PF, Amin N, Bragg-Gresham JL, Teumer A, Glazer NL, Launer L, Zhao JH, Aulchenko Y, Heath S, Sober S, Parsa A, Luan J, Arora P, Dehghan A, Zhang F, Lucas G, Hicks AA, Jackson AU, Peden JF, Tanaka T, Wild SH, Rudan I, Igl W, Milaneschi Y, Parker AN, Fava C, Chambers JC, Fox ER, Kumari M, Go MJ, van der Harst P, Kao WHL, Sjogren M, Vinay DG, Alexander M, Tabara Y, Shaw-Hawkins S, Whincup PH, Liu Y, Shi G, Kuusisto J, Tayo B, Seielstad M, Sim X, Khanh-Dung HN, Lehtimaki T, Matullo G, Wu Y, Gaunt TR, Onland-Moret NC, Cooper MN, Platou CGP, Org E, Hardy R, Dahgam S, Palmen J, Vitart V, Braund PS, Kuznetsova T, Uiterwaal CSPM, Adeyemo A, Palmas W, Campbell H, Ludwig B, Tomaszewski M, Tzoulaki I, Palmer ND, Aspelund T, Garcia M, Chang Y-PC, O'Connell JR, Steinle NI, Grobbee DE, Arking DE, Kardia SL, Morrison AC, Hernandez D, Najjar S, McArdle WL, Hadley D, Brown MJ, Connell JM, Hingorani AD, Day INM, Lawlor DA, Beilby JP, Lawrence RW, Clarke R, Hopewell JC, Ongen H, Dreisbach AW, Li Y, Young JH, Bis JC, Kahonen M, Viikari J, Adair LS, Lee NR, Chen M-H, Olden M, Pattaro C, Bolton JAH, Koettgen A, Bergmann S, Mooser V, Chaturvedi N, Frayling TM, Islam M, Jafar TH, Erdmann J, Kulkarni SR, Bornstein SR, Graessler J, Groop L, Voight BF, Kettunen J, Howard P, Taylor A, Guarrera S, Ricceri F, Emilsson V, Plump A, Barroso IS, Khaw K-T, Weder AB, Hunt SC, Sun YV, Bergman RN, Collins FS, Bonnycastle LL, Scott LJ, Stringham HM, Peltonen L, Perola M, Vartiainen E, Brand S-M, Staessen JA, Wang TJ, Burton PR, Artigas MS, Dong Y, Snieder H, Wang X, Zhu H, Lohman KK, Rudock ME, Heckbert SR, Smith NL, Wiggins KL, Doumatey A, Shriner D, Veldre G, Viigimaa M, Kinra S, Prabhakaran D, Tripathy V, Langefeld CD, Rosengren A, Thelle DS, Corsi AM, Singleton A, Forrester T, Hilton G, McKenzie CA, Salako T, Iwai N, Kita Y, Ogihara T, Ohkubo T, Okamura T, Ueshimet al., 2011, Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk, NATURE, Vol: 478, Pages: 103-109, ISSN: 0028-0836

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• Citations: 1509

Mitson M, Kelley LA, Sternberg MJE, Higgs DR, Gibbons RJet al., 2011, Functional significance of mutations in the Snf2 domain of ATRX, HUMAN MOLECULAR GENETICS, Vol: 20, Pages: 2603-2610, ISSN: 0964-6906

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• Citations: 37

Wass MN, David A, Sternberg MJE, 2011, Challenges for the prediction of macromolecular interactions, CURRENT OPINION IN STRUCTURAL BIOLOGY, Vol: 21, Pages: 382-390, ISSN: 0959-440X

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• Citations: 67

Muggleton SH, Chen J, Watanabe H, Dunbar SJ, Baxter C, Currie R, Salazar JD, Taubert J, Sternberg MJEet al., 2011, Variation of Background Knowledge in an Industrial Application of ILP, 20th International Conference on Inductive Logic Programming (ILP), Publisher: SPRINGER-VERLAG BERLIN, Pages: 158-170, ISSN: 0302-9743

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• Citations: 1