Thomas Conway

1.4k citations
16 papers · 599 · h-index 11

Impact in

Papers in

    • Genomics and Phylogenetic Studies 8
    • Genomics and Chromatin Dynamics 2
    • RNA and protein synthesis mechanisms 2
    • Algorithms and Data Compression 2
    • Natural Language Processing Techniques 1

Thomas Conway

16 papers receiving 567 citations

Peers

Thomas Conway
Comparison fields: 5 of 81
  • Software 34
  • Molecular Medicine 39
  • Artificial Intelligence 222
  • Hardware and Architecture 40
  • Endocrinology 28
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Niko Välimäki Finland
Gilles Bernot France
Vladimir Ulyantsev Russia
Aditi Gupta United States
Philip J. Hatcher United States
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Citations per field
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Citations per year

Countries citing papers authored by Thomas Conway

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Conway

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Thomas Conway, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Thomas Conway Line = papers co-authored together Thomas Conway links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 1996132
2 201180
3 201175
4 201266
5 201159
6 201447
7 201635
8 201032
9 200721
10 201719
11 201214
12
The Implementation of Mercury, an Efficient Purely Declarative Logic Programming Language.
19947
13 20214
14 20224
15 20112
16
The Mercury Language Reference Manual
20162

About Thomas Conway

Thomas Conway is a scholar working on Molecular Biology, Artificial Intelligence, Genetics, Infectious Diseases and Computational Theory and Mathematics, having authored 16 papers that have together received 599 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (8 papers), Tuberculosis Research and Epidemiology (2 papers), Genomics and Chromatin Dynamics (2 papers), Cancer Genomics and Diagnostics (2 papers), RNA and protein synthesis mechanisms (2 papers), Genomics and Rare Diseases (2 papers), Algorithms and Data Compression (2 papers) and Natural Language Processing Techniques (1 paper). The work is most often cited by research in Software (34 citations), Molecular Medicine (39 citations), Artificial Intelligence (222 citations), Hardware and Architecture (40 citations) and Endocrinology (28 citations). Thomas Conway has collaborated with scholars based in Australia, United States and Switzerland. Frequent co-authors include Fergus Henderson, Zoltán Somogyi, Justin Zobel, Bryan Beresford‐Smith, Kathryn E. Holt, Michael Inouye, Kelly L. Wyres, Jan Schröder, James Bailey and Matthias Reumann. Their work appears in journals such as Bioinformatics, The Journal of Logic Programming, BMC Medical Genomics, BMC Genomics and EBioMedicine.

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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