Christopher J. Watkins

13.6k total citations · 2 hit papers
14 papers, 9.8k citations indexed

About

Christopher J. Watkins is a scholar working on Artificial Intelligence, Molecular Biology and Materials Chemistry. According to data from OpenAlex, Christopher J. Watkins has authored 14 papers receiving a total of 9.8k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Molecular Biology and 3 papers in Materials Chemistry. Recurrent topics in Christopher J. Watkins's work include Enzyme Structure and Function (3 papers), Bioinformatics and Genomic Networks (2 papers) and Reinforcement Learning in Robotics (2 papers). Christopher J. Watkins is often cited by papers focused on Enzyme Structure and Function (3 papers), Bioinformatics and Genomic Networks (2 papers) and Reinforcement Learning in Robotics (2 papers). Christopher J. Watkins collaborates with scholars based in United Kingdom, Australia and United States. Christopher J. Watkins's co-authors include Peter Dayan, Nello Cristianini, John Shawe‐Taylor, Huma Lodhi, Natascha Bushati, James Smith, David L. Steffen, Neil J. McKenna, Edward S. Chen and Susan G. Hilsenbeck and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and Cancer Research.

In The Last Decade

Christopher J. Watkins

14 papers receiving 9.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Q-learning

1992 6.8k citations Christopher J. Watkins, Peter Dayan Machine Learning profile →
Technical Note: Q-Learning

1992 2.3k citations Christopher J. Watkins, Peter Dayan Machine Learning profile →

Peers

Countries citing papers authored by Christopher J. Watkins

Since Specialization

Citations

This map shows the geographic impact of Christopher J. Watkins'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 J. Watkins with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher J. Watkins more than expected).

Fields of papers citing papers by Christopher J. Watkins

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher J. Watkins. 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 J. Watkins. The network helps show where Christopher J. Watkins may publish in the future.

Co-authorship network of co-authors of Christopher J. Watkins

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher J. Watkins. A scholar is included among the top collaborators of Christopher J. Watkins 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 J. Watkins. Christopher J. Watkins is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

#	Work	Indexed citations
1	Moving beyond MARCO 2023 ·PLoS ONE ·(unknown), Christopher J. Watkins, Janet Newman	2
2	Tools to Ease the Choice and Design of Protein Crystallisation Experiments 2020 ·Crystals ·(unknown), (unknown), (unknown), (unknown), (unknown), Christopher J. Watkins, (unknown), (unknown), Janet Newman	6
3	Classification of crystallization outcomes using deep convolutional neural networks 2018 ·PLoS ONE ·Andrew E. Bruno, Patrick Charbonneau, Janet Newman, Edward H. Snell, David R. So, Vincent Vanhoucke, Christopher J. Watkins, Shawn P. Williams, Julie Wilson	63
4	Yerba mate (Ilex paraguariensis, A. St.-Hil.) de novo transcriptome assembly based on tissue specific genomic expression profiles 2018 ·BMC Genomics ·(unknown), Christopher J. Watkins, (unknown), (unknown), (unknown), Cristian Antonio Rojas, (unknown), Julián A. Ferreras, Mario Cáccamo, Marcos Miretti	10
5	Evaluating different landmark positioning systems within the RIDE architecture 2013 ·LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) ·(unknown), Christopher J. Watkins, (unknown), (unknown)	8
6	An intuitive graphical visualization technique for the interrogation of transcriptome data 2011 ·Nucleic Acids Research ·Natascha Bushati, James Smith, James Briscoe, Christopher J. Watkins	37
7	Example-based speech recognition using formulaic phrases 2009 ·Christopher J. Watkins, Stephen Cox	1
8	GEMS (Gene Expression Metasignatures), a Web Resource for Querying Meta-analysis of Expression Microarray Datasets: 17β-Estradiol in MCF-7 Cells 2008 ·Cancer Research ·Scott A. Ochsner, David L. Steffen, Susan G. Hilsenbeck, Edward S. Chen, Christopher J. Watkins, Neil J. McKenna	54
9	Text Classification using String Kernels 2000 ·Bristol Research (University of Bristol) ·Huma Lodhi, John Shawe‐Taylor, Nello Cristianini, Christopher J. Watkins	376
10	Differences in meanings of health: an exploratory study of general practitioners and their patients 1996 ·Family Practice ·(unknown), Christopher J. Watkins, (unknown)	33
11	Technical Note:Q-Learning 1993 ·UCL Discovery (University College London) ·Christopher J. Watkins	90
12	Technical Note: Q-Learning breakdown → 1992 ·Machine Learning ·Christopher J. Watkins, Peter Dayan	2318
13	Q-learning breakdown → 1992 ·Machine Learning ·Christopher J. Watkins, Peter Dayan	6772
14	Combining Cross-Validation and Search. 1987 ·Christopher J. Watkins	9

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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