Goran Neshich

1.1k citations
48 papers · 756 · h-index 19

Impact in

    • Protein Structure and Dynamics
    • Machine Learning in Bioinformatics
    • RNA and protein synthesis mechanisms
    • Biochemical and Structural Characterization
    • Genomics and Phylogenetic Studies

Papers in

    • Protein Structure and Dynamics 17
    • RNA and protein synthesis mechanisms 10
    • Machine Learning in Bioinformatics 9
    • Genomics and Phylogenetic Studies 8
    • Biochemical and Structural Characterization 8
    • Enzyme Structure and Function 9

Goran Neshich

44 papers receiving 732 citations

Peers

Goran Neshich
Comparison fields: 5 of 95
  • Biotechnology 79
  • Molecular Biology 536
  • Computational Theory and Mathematics 87
  • Microbiology 34
  • Virology 25
Replace Bong-Hyun Kim with:
Bong-Hyun Kim United States
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Citations per field
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Citations per year

Countries citing papers authored by Goran Neshich

Since Specialization
Citations

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

Fields of papers citing papers by Goran Neshich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Goran Neshich, 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 Goran Neshich Line = papers co-authored together Goran Neshich links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200870
2 200356
3 200036
4
Predicting enzyme class from protein structure using Bayesian classification.
200636
5 200535
6
Using bradykinin-potentiating peptide structures to develop new antihypertensive drugs.
200434
7 200432
8 199729
9 200429
10 200328
11 201327
12 199527
13 199724
14 200723
15 201822
16 200421
17 200718
18 200418
19
The Star STING server: a multiplatform environment for protein structure analysis.
200618
20 201317

About Goran Neshich

Goran Neshich is a scholar working on Molecular Biology, Materials Chemistry, Biotechnology, Genetics and Plant Science, having authored 48 papers that have together received 756 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (17 papers), RNA and protein synthesis mechanisms (10 papers), Machine Learning in Bioinformatics (9 papers), Enzyme Structure and Function (9 papers), Genomics and Phylogenetic Studies (8 papers), Biochemical and Structural Characterization (8 papers), Enzyme Production and Characterization (7 papers) and Venomous Animal Envenomation and Studies (5 papers). The work is most often cited by research in Biotechnology (79 citations), Molecular Biology (536 citations), Computational Theory and Mathematics (87 citations), Microbiology (34 citations) and Virology (25 citations). Goran Neshich has collaborated with scholars based in Brazil, Sudan and United Kingdom. Frequent co-authors include Roberto Coiti Togawa, Jorge Hernández Fernández, Antônio Carlos Martins de Camargo, Paula R. Kuser, M. E. B. Yamagishi, R. H. Higa, Luciane V. Mello, Marcelo M. Santoro, Maria Fátima Grossi‐de‐Sá and Wagner Meira. Their work appears in journals such as Bioinformatics, Nucleic Acids Research, PLoS ONE, FEBS Letters and PLoS Computational Biology.

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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