K.‐L. Ting

440 citations
18 papers · 363 · h-index 10

Impact in

    • Protein Structure and Dynamics
    • RNA and protein synthesis mechanisms
    • DNA and Nucleic Acid Chemistry
    • Machine Learning in Bioinformatics
    • Advanced biosensing and bioanalysis techniques

Papers in

K.‐L. Ting

18 papers receiving 344 citations

Peers

K.‐L. Ting
Comparison fields: 5 of 78
  • Molecular Biology 255
  • Filtration and Separation 6
  • Physical and Theoretical Chemistry 22
  • Spectroscopy 23
  • Computational Theory and Mathematics 23
Replace Shigeyoshi Nakamura with:
Shigeyoshi Nakamura Japan
В. И. Воробьев Russia
Arghya Chakravorty United States
Masahiko Hiraki Japan
Till Briskot Germany
Hendrik Jung Germany
Aashish Kumar Jain United States
Ian C. Nova United States
Wai Shing Tang United States
Catalina O. Tudor United States
K.‐L. Ting relative to Shigeyoshi Nakamura Japan Shigeyoshi Nakamura's profile →
Citations per field
00.5×2×3×3.8×
Shigeyoshi Nakamura · 1×
Citations per year

Countries citing papers authored by K.‐L. Ting

Since Specialization
Citations

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

Fields of papers citing papers by K.‐L. Ting

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by K.‐L. Ting. 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 K.‐L. Ting. The network helps show where K.‐L. Ting may publish in the future.

Co-authors

The 24 scholars most cited alongside K.‐L. Ting, 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 K.‐L. Ting Line = papers co-authored together K.‐L. Ting links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2002124
2 198638
3 198933
4 199030
5 200221
6 199416
7 200815
8 198913
9 199212
10 197912
11 200610
12 19837
13 19947
14 19757
15 19906
16 19984
17 19834
18 19914

About K.‐L. Ting

K.‐L. Ting is a scholar working on Molecular Biology, Physical and Theoretical Chemistry, Computational Mechanics, Industrial and Manufacturing Engineering and Spectroscopy, having authored 18 papers that have together received 363 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), DNA and Nucleic Acid Chemistry (4 papers), RNA and protein synthesis mechanisms (3 papers), Machine Learning in Bioinformatics (2 papers), thermodynamics and calorimetric analyses (2 papers), Analytical Chemistry and Chromatography (2 papers), Manufacturing Process and Optimization (2 papers) and Enzyme Structure and Function (2 papers). The work is most often cited by research in Molecular Biology (255 citations), Filtration and Separation (6 citations), Physical and Theoretical Chemistry (22 citations), Spectroscopy (23 citations) and Computational Theory and Mathematics (23 citations). K.‐L. Ting has collaborated with scholars based in United States, Israel and Taiwan. Frequent co-authors include Robert L. Jernigan, Andrzej Kloczkowski, Jean-Pierre Garnier, Arieh Y. Ben-Naim, Akinori Sarai, Ruth Nussinov, A. H. Soni, Gopalan Raghunathan, Sheng Jiang and Zhiqi Liu. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Biopolymers, Materials Science and Engineering A, Mechanism and Machine Theory and Computers in Biology and Medicine.

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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