Thomas Litfin

1.8k total citations
27 papers, 859 citations indexed

About

Thomas Litfin is a scholar working on Molecular Biology, Materials Chemistry and Organic Chemistry. According to data from OpenAlex, Thomas Litfin has authored 27 papers receiving a total of 859 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 7 papers in Materials Chemistry and 2 papers in Organic Chemistry. Recurrent topics in Thomas Litfin's work include RNA and protein synthesis mechanisms (14 papers), Machine Learning in Bioinformatics (10 papers) and Protein Structure and Dynamics (10 papers). Thomas Litfin is often cited by papers focused on RNA and protein synthesis mechanisms (14 papers), Machine Learning in Bioinformatics (10 papers) and Protein Structure and Dynamics (10 papers). Thomas Litfin collaborates with scholars based in Australia, China and United States. Thomas Litfin's co-authors include Yaoqi Zhou, Kuldip K. Paliwal, Jack Hanson, Yuedong Yang, Jaswinder Singh, Jaspreet Singh, Jian Zhan, Tongchuan Zhang, Thomas Haselhorst and Joe Tiralongo and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Bioinformatics.

In The Last Decade

Thomas Litfin

25 papers receiving 851 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Thomas Litfin Australia 16 758 178 111 26 25 27 859
Elisa Cilia Belgium 9 446 0.6× 86 0.5× 64 0.6× 81 3.1× 30 1.2× 18 553
Raphaël A. G. Chaleil United Kingdom 11 757 1.0× 188 1.1× 247 2.2× 42 1.6× 53 2.1× 19 1.0k
Mattia Miotto Italy 13 353 0.5× 81 0.5× 71 0.6× 23 0.9× 23 0.9× 38 524
Julie Bernauer France 11 422 0.6× 132 0.7× 77 0.7× 12 0.5× 13 0.5× 24 464
Noelia Ferruz Spain 12 652 0.9× 131 0.7× 117 1.1× 40 1.5× 15 0.6× 20 818
Roland A. Pache Spain 12 580 0.8× 104 0.6× 80 0.7× 39 1.5× 73 2.9× 19 703
Yan Yuan Tseng United States 14 441 0.6× 106 0.6× 73 0.7× 53 2.0× 26 1.0× 37 548
Gisela Gabernet Switzerland 15 494 0.7× 51 0.3× 114 1.0× 22 0.8× 9 0.4× 33 785
Peter Vanhee Spain 8 616 0.8× 91 0.5× 104 0.9× 87 3.3× 33 1.3× 10 710
Elke Michalsky Germany 12 384 0.5× 104 0.6× 78 0.7× 57 2.2× 18 0.7× 18 524

Countries citing papers authored by Thomas Litfin

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Litfin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Litfin

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

All Works

20 of 20 papers shown
1.
Litfin, Thomas, Lou Brillault, Veronika Masic, et al.. (2025). Molecular characterisation of the Bacillus subtilis SpbK antiphage defence system. Nature Communications. 17(1). 1051–1051.
2.
Chen, Ke, Thomas Litfin, Jaswinder Singh, Jian Zhan, & Yaoqi Zhou. (2024). MARS and RNAcmap3: The Master Database of All Possible RNA Sequences Integrated with RNAcmap for RNA Homology Search. Genomics Proteomics & Bioinformatics. 22(1). 6 indexed citations
3.
Litfin, Thomas, Viola Heinzelmann‐Schwarz, Tobias Lange, et al.. (2024). Highly Sensitive Spatial Glycomics at Near-Cellular Resolution by On-Slide Derivatization and Mass Spectrometry Imaging. Analytical Chemistry. 96(28). 11163–11171. 8 indexed citations
4.
Zhou, Yaoqi, Thomas Litfin, & Jian Zhan. (2023). 3 = 1 + 2: how the divide conquered de novo protein structure prediction and what is next?. National Science Review. 10(12). 6 indexed citations
5.
Xu, Fan, Thomas Litfin, Ke Chen, et al.. (2023). Multiple sequence alignment-based RNA language model and its application to structural inference. Nucleic Acids Research. 52(1). e3–e3. 45 indexed citations
6.
Singh, Jaspreet, Thomas Litfin, Jaswinder Singh, Kuldip K. Paliwal, & Yaoqi Zhou. (2022). SPOT-Contact-LM: improving single-sequence-based prediction of protein contact map using a transformer language model. Bioinformatics. 38(7). 1888–1894. 34 indexed citations
7.
Singh, Jaspreet, Kuldip K. Paliwal, Thomas Litfin, Jaswinder Singh, & Yaoqi Zhou. (2022). Reaching alignment-profile-based accuracy in predicting protein secondary and tertiary structural properties without alignment. Scientific Reports. 12(1). 7607–7607. 32 indexed citations
8.
Zhou, Kai, Thomas Litfin, Md. Solayman, et al.. (2022). High-throughput split-protein profiling by combining transposon mutagenesis and regulated protein-protein interactions with deep sequencing. International Journal of Biological Macromolecules. 203. 543–552.
9.
10.
Zhang, Tongchuan, Jaswinder Singh, Thomas Litfin, et al.. (2021). RNAcmap: a fully automatic pipeline for predicting contact maps of RNAs by evolutionary coupling analysis. Bioinformatics. 37(20). 3494–3500. 26 indexed citations
11.
12.
Singh, Jaswinder, Kuldip K. Paliwal, Tongchuan Zhang, et al.. (2021). Improved RNA secondary structure and tertiary base-pairing prediction using evolutionary profile, mutational coupling and two-dimensional transfer learning. Bioinformatics. 37(17). 2589–2600. 63 indexed citations
13.
14.
Cai, Yufeng, Zhe Sun, Yutong Lu, et al.. (2019). SPOT‐Fold: Fragment‐Free Protein Structure Prediction Guided by Predicted Backbone Structure and Contact Map. Journal of Computational Chemistry. 41(8). 745–750. 9 indexed citations
15.
Hanson, Jack, Kuldip K. Paliwal, Thomas Litfin, Yuedong Yang, & Yaoqi Zhou. (2019). Getting to Know Your Neighbor: Protein Structure Prediction Comes of Age with Contextual Machine Learning. Journal of Computational Biology. 27(5). 796–814. 15 indexed citations
16.
Litfin, Thomas, et al.. (2019). Nucleotide Sugar Transporter SLC35 Family Structure and Function. Computational and Structural Biotechnology Journal. 17. 1123–1134. 64 indexed citations
17.
Hanson, Jack, Thomas Litfin, Kuldip K. Paliwal, & Yaoqi Zhou. (2019). Identifying molecular recognition features in intrinsically disordered regions of proteins by transfer learning. Bioinformatics. 36(4). 1107–1113. 38 indexed citations
18.
Tiralongo, Joe, Thomas Litfin, Yuedong Yang, et al.. (2018). YesU from Bacillus subtilis preferentially binds fucosylated glycans. Scientific Reports. 8(1). 13139–13139. 5 indexed citations
19.
Litfin, Thomas, Yaoqi Zhou, & Yuedong Yang. (2017). SPOT-ligand 2: improving structure-based virtual screening by binding-homology search on an expanded structural template library. Bioinformatics. 33(8). 1238–1240. 17 indexed citations
20.
Litfin, Thomas, et al.. (2016). Non-steroidal anti-inflammatories and the development of analgesic nephropathy: a systematic review. Renal Failure. 38(9). 1328–1334. 13 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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