Jacob Carter

516 total citations
10 papers, 110 citations indexed

About

Jacob Carter is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, Jacob Carter has authored 10 papers receiving a total of 110 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Molecular Biology and 1 paper in Information Systems. Recurrent topics in Jacob Carter's work include Biomedical Text Mining and Ontologies (7 papers), Semantic Web and Ontologies (7 papers) and Topic Modeling (3 papers). Jacob Carter is often cited by papers focused on Biomedical Text Mining and Ontologies (7 papers), Semantic Web and Ontologies (7 papers) and Topic Modeling (3 papers). Jacob Carter collaborates with scholars based in United Kingdom, United States and Mexico. Jacob Carter's co-authors include Sophia Ananiadou, Riza Batista-Navarro, Rohit Thummalapalli, David A. Barbie, Russell W. Jenkins, Israel Cañadas, Paul M. Thompson, John McNaught, Rafał Rak and Andrew Rowley and has published in prestigious journals such as PLoS ONE, Annual Review of Medicine and Proceedings of the VLDB Endowment.

In The Last Decade

Jacob Carter

9 papers receiving 107 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jacob Carter United Kingdom	5	48	48	22	16	10	10	110
Tianhan Dong United States	6	62 1.3×	32 0.7×	17 0.8×	11 0.7×	19 1.9×	7	173
Susanne Kimeswenger Austria	7	30 0.6×	23 0.5×	31 1.4×	17 1.1×	6 0.6×	15	131
Chu‐Cheng Lin Taiwan	7	64 1.3×	120 2.5×	7 0.3×	11 0.7×	3 0.3×	19	199
Nicolas Sompairac France	5	74 1.5×	12 0.3×	20 0.9×	24 1.5×	8 0.8×	7	114
Lea Seep Germany	4	60 1.3×	21 0.4×	12 0.5×	25 1.6×	6 0.6×	6	115
Leonid Kvecher United States	6	49 1.0×	30 0.6×	33 1.5×	4 0.3×	17 1.7×	13	128
Margherita Berardi Italy	8	36 0.8×	26 0.5×	15 0.7×	10 0.6×	5 0.5×	22	141
Christian Köhler Germany	7	100 2.1×	22 0.5×	8 0.4×	10 0.6×	8 0.8×	18	191
Yujia Bao United States	7	48 1.0×	100 2.1×	13 0.6×	4 0.3×	7 0.7×	10	188
Licheng Wu China	8	169 3.5×	24 0.5×	14 0.6×	5 0.3×	13 1.3×	16	216

Countries citing papers authored by Jacob Carter

Since Specialization

Citations

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

Fields of papers citing papers by Jacob Carter

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jacob Carter. 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 Jacob Carter. The network helps show where Jacob Carter may publish in the future.

Co-authorship network of co-authors of Jacob Carter

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

All Works

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10 of 10 papers shown

1.

Carter, Jacob, et al.. (2024). Nitro: Boosting Distributed Reinforcement Learning with Serverless Computing. Proceedings of the VLDB Endowment. 18(1). 66–79.

2.

Jenkins, Russell W., Rohit Thummalapalli, Jacob Carter, Israel Cañadas, & David A. Barbie. (2017). Molecular and Genomic Determinants of Response to Immune Checkpoint Inhibition in Cancer. Annual Review of Medicine. 69(1). 333–347. 35 indexed citations

3.

Thompson, Paul M., Riza Batista-Navarro, Georgios Kontonatsios, et al.. (2016). Text Mining the History of Medicine. PLoS ONE. 11(1). e0144717–e0144717. 37 indexed citations

4.

Batista-Navarro, Riza, Jacob Carter, & Sophia Ananiadou. (2016). Argo: enabling the development of bespoke workflows and services for disease annotation. Database. 2016. baw066–baw066. 10 indexed citations

5.

Batista-Navarro, Riza, Jacob Carter, & Sophia Ananiadou. (2015). Development of bespoke machine learning and biocuration workflows in a BioC-supporting text mining workbench.. Research Explorer (The University of Manchester). 51–56. 1 indexed citations

6.

Thompson, Paul M., Jacob Carter, John McNaught, & Sophia Ananiadou. (2015). Semantically enhanced search system for historical medical archives. Research Explorer (The University of Manchester). 387–390. 3 indexed citations

7.

Batista-Navarro, Riza, Jacob Carter, & Sophia Ananiadou. (2015). Semi-automatic curation of chronic obstructive pulmonary disease phenotypes using Argo.. Research Explorer (The University of Manchester). 406–408. 1 indexed citations

8.

Rak, Rafał, Jacob Carter, Andrew Rowley, Riza Batista-Navarro, & Sophia Ananiadou. (2014). Interoperability and Customisation of Annotation Schemata in Argo. Language Resources and Evaluation. 3837–3842. 2 indexed citations

9.

Rak, Rafał, Riza Batista-Navarro, Andrew Rowley, Jacob Carter, & Sophia Ananiadou. (2014). Text-mining-assisted biocuration workflows in Argo. Database. 2014. 15 indexed citations

10.

Rak, Rafał, Andrew Rowley, Jacob Carter, & Sophia Ananiadou. (2013). Development and Analysis of NLP Pipelines in Argo. Research Explorer (The University of Manchester). 115–120. 6 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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