Christopher H. Bryant

978 total citations
16 papers, 496 citations indexed

About

Christopher H. Bryant is a scholar working on Molecular Biology, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Christopher H. Bryant has authored 16 papers receiving a total of 496 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 8 papers in Artificial Intelligence and 3 papers in Computational Theory and Mathematics. Recurrent topics in Christopher H. Bryant's work include Bioinformatics and Genomic Networks (5 papers), Microbial Metabolic Engineering and Bioproduction (5 papers) and Analytical Chemistry and Chromatography (3 papers). Christopher H. Bryant is often cited by papers focused on Bioinformatics and Genomic Networks (5 papers), Microbial Metabolic Engineering and Bioproduction (5 papers) and Analytical Chemistry and Chromatography (3 papers). Christopher H. Bryant collaborates with scholars based in United Kingdom, Sweden and Jordan. Christopher H. Bryant's co-authors include Philip G. K. Reiser, Stephen Muggleton, Stephen G. Oliver, Ross D. King, Douglas B. Kell, Ffion Mair Jones, Kenneth E. Whelan, R.C. Rowe, R.C. Rowe and Alison Adam and has published in prestigious journals such as Nature, Analytica Chimica Acta and BMC Bioinformatics.

In The Last Decade

Christopher H. Bryant

16 papers receiving 456 citations

Peers

Christopher H. Bryant

CTM

Philip G. K. Reiser New Zealand

Ffion Mair Jones United Kingdom

Emma Byrne United Kingdom

Kurt De Grave Belgium

Yongfeng Gu United States

Bruce S. Duncan United States

Joseph M. Lancaster United States

Tom VanCourt United States

Saurabh Srivastava India

Philip G. K. Reiser New Zealand

Christopher H. Bryant

198 ×0.8

167 ×0.9

72 ×0.8

CTM

44 ×0.8

49 ×0.9

Citations per year, relative to Christopher H. Bryant Christopher H. Bryant (= 1×) peers Philip G. K. Reiser

Countries citing papers authored by Christopher H. Bryant

Since Specialization

Citations

This map shows the geographic impact of Christopher H. Bryant's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Christopher H. Bryant with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher H. Bryant more than expected).

Fields of papers citing papers by Christopher H. Bryant

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher H. Bryant. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Christopher H. Bryant. The network helps show where Christopher H. Bryant may publish in the future.

Co-authorship network of co-authors of Christopher H. Bryant

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher H. Bryant. A scholar is included among the top collaborators of Christopher H. Bryant based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Christopher H. Bryant. Christopher H. Bryant is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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16 of 16 papers shown

Bryant, Christopher H., et al.. (2015). Pruning Classification Rules with Instance Reduction Methods. International Journal of Machine Learning and Computing. 5(3). 187–191. 2 indexed citations

Selpi, Selpi, et al.. (2009). Predicting functional upstream open reading frames in Saccharomyces cerevisiae. BMC Bioinformatics. 10(1). 451–451. 9 indexed citations

Ray, Oliver & Christopher H. Bryant. (2008). Inferring the Function of Genes from Synthetic Lethal Mutations. University of Salford Institutional Repository (University of Salford). 5. 667–671. 4 indexed citations

Selpi, Selpi, Christopher H. Bryant, Graham J. Kemp, & Marija Cvijović. (2007). A First Step towards Learning which uORFs Regulate Gene Expression. University of Salford Institutional Repository (University of Salford). 3 indexed citations

Bryant, Christopher H., et al.. (2006). A First Step towards Learning which uORFs Regulate Gene Expression. Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics. 3(2). 109–122. 1 indexed citations

King, Ross D., Kenneth E. Whelan, Ffion Mair Jones, et al.. (2004). Functional genomic hypothesis generation and experimentation by a robot scientist. Nature. 427(6971). 247–252. 389 indexed citations

Bryant, Christopher H., et al.. (2001). Combining inductive logic programming, active learning and robotics to discover the function of genes. University of Salford Institutional Repository (University of Salford). 5. 1–36. 23 indexed citations

Reiser, Philip G. K., Ross D. King, Douglas B. Kell, et al.. (2001). Developing a logical model of yeast metabolism. University of Salford Institutional Repository (University of Salford). 5. 223–244. 14 indexed citations

Muggleton, Stephen, Christopher H. Bryant, Ashwin Srinivasan, et al.. (2001). Are Grammatical Representations Useful for Learning from Biological Sequence Data?— A Case Study. Journal of Computational Biology. 8(5). 493–521. 13 indexed citations

10.

Muggleton, Stephen, Christopher H. Bryant, & Ashwin Srinivasan. (2000). Learning Chomsky-like Grammars for Biological Sequence Families. University of Salford Institutional Repository (University of Salford). 631–638. 3 indexed citations

11.

Bryant, Christopher H. & R.C. Rowe. (1998). Knowledge discovery in databases: application to chromatography. TrAC Trends in Analytical Chemistry. 17(1). 18–24. 4 indexed citations

12.

Bryant, Christopher H., et al.. (1997). Transforming general program proofs: a meta interpreter which expands negative literals. Clinical and Experimental Rheumatology. 26(3). 509–10. 3 indexed citations

13.

Bryant, Christopher H., Alison Adam, David R. Taylor, & R.C. Rowe. (1997). Using inductive logic programming to discover knowledge hidden in chemical data. Chemometrics and Intelligent Laboratory Systems. 36(2). 111–123. 2 indexed citations

14.

Bryant, Christopher H., Alison Adam, David R. Taylor, & R.C. Rowe. (1996). Towards an expert system for enantioseparations: induction of rules using machine learning. Chemometrics and Intelligent Laboratory Systems. 34(1). 21–40. 9 indexed citations

15.

McCluskey, T.L., et al.. (1996). The Validation of Formal Specifications of Requirements. Electronic workshops in computing. 2 indexed citations

16.

Bryant, Christopher H., et al.. (1994). A review of expert systems for chromatography. Analytica Chimica Acta. 297(3). 317–347. 15 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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