Samuel Selvaraj

569 total citations
24 papers, 409 citations indexed

About

Samuel Selvaraj is a scholar working on Molecular Biology, Materials Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Samuel Selvaraj has authored 24 papers receiving a total of 409 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 10 papers in Materials Chemistry and 7 papers in Computational Theory and Mathematics. Recurrent topics in Samuel Selvaraj's work include Protein Structure and Dynamics (19 papers), RNA and protein synthesis mechanisms (12 papers) and Enzyme Structure and Function (10 papers). Samuel Selvaraj is often cited by papers focused on Protein Structure and Dynamics (19 papers), RNA and protein synthesis mechanisms (12 papers) and Enzyme Structure and Function (10 papers). Samuel Selvaraj collaborates with scholars based in India, Japan and United States. Samuel Selvaraj's co-authors include Akinori Sarai, Hidetoshi Kono, M. Michael Gromiha, Konda Mani Saravanan, István Simon, Gerard Pujadas, Csaba Magyar, Hatsuho Uedaira, Ponraj Prabakaran and Jianghong An and has published in prestigious journals such as Bioinformatics, Journal of Molecular Biology and Gene.

In The Last Decade

Samuel Selvaraj

24 papers receiving 406 citations

Peers

Samuel Selvaraj

CTM

GENET

ECOLO

Alessio Del Conte Italy

Jon A. Christopher United States

Sara Cheek United States

Harpreet Kaur India

Barbara Lelj‐Garolla Canada

S.H. Sleigh United Kingdom

Daniela Bonetti Italy

Susana Barrera-Vilarmau Spain

Mark A. Hallen United States

Jack W. Heal United Kingdom

Alessio Del Conte Italy

Samuel Selvaraj

237 ×0.6

42 ×0.4

30 ×0.7

CTM

19 ×0.7

GENET

14 ×0.7

ECOLO

Citations per year, relative to Samuel Selvaraj Samuel Selvaraj (= 1×) peers Alessio Del Conte

Countries citing papers authored by Samuel Selvaraj

Since Specialization

Citations

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

Fields of papers citing papers by Samuel Selvaraj

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samuel Selvaraj

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

All Works

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20 of 20 papers shown

Parthasarathy, S., et al.. (2019). Identification and Analysis of Long Repeats of Proteins at the Domain Level. Frontiers in Bioengineering and Biotechnology. 7. 250–250. 4 indexed citations

Saravanan, Konda Mani & Samuel Selvaraj. (2017). Dihedral angle preferences of amino acid residues forming various non-local interactions in proteins. Journal of Biological Physics. 43(2). 265–278. 18 indexed citations

Selvaraj, Samuel, et al.. (2016). Prediction of kinase-inhibitor binding affinity using energetic parameters. Bioinformation. 12(3). 172–181. 1 indexed citations

Selvaraj, Samuel & Konda Mani Saravanan. (2015). Better theoretical models and protein design experiments can help to understand protein folding. Journal of Natural Science Biology and Medicine. 6(1). 202–202. 2 indexed citations

Saravanan, Konda Mani, et al.. (2014). Conservation of inter-residue interactions and prediction of folding rates of domain repeats. Journal of Biomolecular Structure and Dynamics. 33(3). 534–551. 3 indexed citations

Selvaraj, Samuel, et al.. (2013). Analysis of sequence repeats of proteins in the PDB. Computational Biology and Chemistry. 47. 156–166. 11 indexed citations

Saravanan, Konda Mani & Samuel Selvaraj. (2013). Search and Analysis of Identical Reverse Octapeptides in Unrelated Proteins. Genomics Proteomics & Bioinformatics. 11(2). 114–121. 2 indexed citations

Nallusamy, Saranya & Samuel Selvaraj. (2012). QSAR Studies on HIV-1 Protease Inhibitors Using Non-Linearly Transformed Descriptors. Current Computer - Aided Drug Design. 8(1). 10–49. 6 indexed citations

Selvaraj, Samuel, et al.. (2012). Role of Long-Range Contacts and Structural Classification in Understanding the Free Energy of Unfolding of Two-State Proteins. Current Bioinformatics. 7(2). 143–151. 1 indexed citations

10.

Saravanan, Konda Mani & Samuel Selvaraj. (2012). Performance of secondary structure prediction methods on proteins containing structurally ambivalent sequence fragments. Biopolymers. 100(2). 148–153. 10 indexed citations

11.

Nallusamy, Saranya & Samuel Selvaraj. (2011). Role of Interactions and Volume Variation in Discriminating Active and Inactive Forms of Cyclin‐Dependent Kinase‐2 Inhibitor Complexes. Chemical Biology & Drug Design. 78(3). 361–369. 3 indexed citations

12.

Gromiha, M. Michael, et al.. (2005). Role of inter and intramolecular interactions in protein–DNA recognition. Gene. 364. 108–113. 25 indexed citations

13.

Gromiha, M. Michael, et al.. (2004). Intermolecular and Intramolecular Readout Mechanisms in Protein–DNA Recognition. Journal of Molecular Biology. 337(2). 285–294. 102 indexed citations

14.

Gromiha, M. Michael, Gerard Pujadas, Csaba Magyar, Samuel Selvaraj, & István Simon. (2004). Locating the stabilizing residues in (α/β)₈ barrel proteins based on hydrophobicity, long‐range interactions, and sequence conservation. Proteins Structure Function and Bioinformatics. 55(2). 316–329. 70 indexed citations

15.

Gromiha, M. Michael & Samuel Selvaraj. (2002). Importance of Long-Range Interactions for Determining the Folding Rate and Transition State Structures of Two-state Proteins. Proceedings Genome Informatics Workshop/Genome informatics. 13. 348–349. 2 indexed citations

16.

Selvaraj, Samuel, Hidetoshi Kono, & Akinori Sarai. (2002). Specificity of Protein–DNA Recognition Revealed by Structure-based Potentials: Symmetric/Asymmetric and Cognate/Non-cognate Binding. Journal of Molecular Biology. 322(5). 907–915. 56 indexed citations

17.

Dehouck, Yves, Marianne Rooman, Dimitri Gilis, M. Michael Gromiha, & Samuel Selvaraj. (2002). In silico protein folding: recent developments. Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles). 151–166. 1 indexed citations

18.

Sarai, Akinori, M. Michael Gromiha, Jianghong An, et al.. (2001). Thermodynamic databases for proteins and protein-nucleic acid interactions. Biopolymers. 61(2). 121–126. 18 indexed citations

19.

Prabakaran, Ponraj, Jianghong An, M. Michael Gromiha, et al.. (2001). Thermodynamic database for protein–nucleic acid interactions (ProNIT). Bioinformatics. 17(11). 1027–1034. 56 indexed citations

20.

Prabakaran, Ponraj, Jungeun An, M. Michael Gromiha, et al.. (2001). 3P104Update of ProNIT : Thermodynamic Database for Protein-Nucleic Acid Interactions. Seibutsu Butsuri. 41(supplement). S184–S184. 2 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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