Tina Perica

6.2k total citations
12 papers, 551 citations indexed

About

Tina Perica is a scholar working on Molecular Biology, Materials Chemistry and Pharmacology. According to data from OpenAlex, Tina Perica has authored 12 papers receiving a total of 551 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 3 papers in Materials Chemistry and 1 paper in Pharmacology. Recurrent topics in Tina Perica's work include Protein Structure and Dynamics (8 papers), RNA and protein synthesis mechanisms (6 papers) and Bioinformatics and Genomic Networks (3 papers). Tina Perica is often cited by papers focused on Protein Structure and Dynamics (8 papers), RNA and protein synthesis mechanisms (6 papers) and Bioinformatics and Genomic Networks (3 papers). Tina Perica collaborates with scholars based in United Kingdom, United States and Norway. Tina Perica's co-authors include Sarah A. Teichmann, Joseph A. Marsh, Sebastian E. Ahnert, Cyrus Chothia, Helena Hernández, Zoe Hall, Carol V. Robinson, Xiuwei Zhang, Lucy J. Colwell and Filipa L. Sousa and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Tina Perica

12 papers receiving 548 citations

Peers

Tina Perica

MB

MC

GENET

CB

SPECT

R. Gonzalo Parra Argentina

Adrian A. Nickson United Kingdom

Tony A. Klink United States

Claudia Bertonati Italy

Ganesh Iyer United States

Abbas Razvi United States

Manca Kenig Slovenia

Vy Nguyen United States

Eric A. First United States

Johanne Le Coq Spain

R. Gonzalo Parra Argentina

Tina Perica

568 ×1.2

MB

144 ×0.9

MC

81 ×1.4

GENET

47 ×0.9

CB

32 ×0.8

SPECT

Citations per year, relative to Tina Perica Tina Perica (= 1×) peers R. Gonzalo Parra

Countries citing papers authored by Tina Perica

Since Specialization

Citations

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

Fields of papers citing papers by Tina Perica

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tina Perica

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

All Works

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12 of 12 papers shown

1.

Perica, Tina, et al.. (2024). Biochemistry and genetics are coming together to improve our understanding of genotype to phenotype relationships. Current Opinion in Structural Biology. 89. 102952–102952. 1 indexed citations

2.

Mathy, Christopher J.P., Parul Mishra, Julia M. Flynn, et al.. (2023). A complete allosteric map of a GTPase switch in its native cellular network. Cell Systems. 14(3). 237–246.e7. 15 indexed citations

3.

Perica, Tina, Christopher J.P. Mathy, Jiewei Xu, et al.. (2021). Systems-level effects of allosteric perturbations to a model molecular switch. Nature. 599(7883). 152–157. 12 indexed citations

4.

Perica, Tina, Yasushi Kondo, Sandhya P. Tiwari, et al.. (2014). Evolution of oligomeric state through allosteric pathways that mimic ligand binding. Science. 346(6216). 1254346–1254346. 60 indexed citations

5.

Marsh, Joseph A., Helena Hernández, Zoe Hall, et al.. (2013). Structural and Evolutionary Dynamics Facilitate Ordered Protein Complex Assembly. Biophysical Journal. 104(2). 391a–391a. 3 indexed citations

6.

Zhang, Xiuwei, Tina Perica, & Sarah A. Teichmann. (2013). Evolution of protein structures and interactions from the perspective of residue contact networks. Current Opinion in Structural Biology. 23(6). 954–963. 32 indexed citations

7.

Roller, Maša, et al.. (2013). Environmental shaping of codon usage and functional adaptation across microbial communities. Nucleic Acids Research. 41(19). 8842–8852. 39 indexed citations

8.

Marsh, Joseph A., Helena Hernández, Zoe Hall, et al.. (2013). Protein Complexes Are under Evolutionary Selection to Assemble via Ordered Pathways. Cell. 153(2). 461–470. 190 indexed citations

9.

Perica, Tina, Cyrus Chothia, & Sarah A. Teichmann. (2012). Evolution of oligomeric state through geometric coupling of protein interfaces. Proceedings of the National Academy of Sciences. 109(21). 8127–8132. 43 indexed citations

10.

Perica, Tina, Joseph A. Marsh, Filipa L. Sousa, et al.. (2012). The emergence of protein complexes: quaternary structure, dynamics and allostery. Biochemical Society Transactions. 40(3). 475–491. 71 indexed citations

11.

Perica, Tina & Cyrus Chothia. (2010). Ubiquitin—molecular mechanisms for recognition of different structures. Current Opinion in Structural Biology. 20(3). 367–376. 29 indexed citations

12.

Crosetto, Nicola, Magda Bienko, Richard G. Hibbert, et al.. (2008). Human Wrnip1 Is Localized in Replication Factories in a Ubiquitin-binding Zinc Finger-dependent Manner. Journal of Biological Chemistry. 283(50). 35173–35185. 56 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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