Shuba Gopal
Impact in
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- Metabolomics and Mass Spectrometry Studies
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
- CRISPR and Genetic Engineering
- Microbial Metabolic Engineering and Bioproduction
- Bioinformatics and Genomic Networks
Papers in
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- RNA and protein synthesis mechanisms 5
- Genomics and Phylogenetic Studies 3
- Advanced biosensing and bioanalysis techniques 1
- Machine Learning in Bioinformatics 1
- Genetics, Bioinformatics, and Biomedical Research 1
- Nuclear Structure and Function 1
- Co-authors
- Terry Gaasterland (3 shared papers)Monica Riley (1 shared paper)Margrethe H. Serres (1 shared paper)Ping Liang (1 shared paper)Laila Alves Nahum (1 shared paper)Clary B. Clish (2 shared papers)Miguel Ángel Martínez‐González (1 shared paper)Justin Scott (1 shared paper)
- Journals
- Genome biology (3 papers)Nature Genetics (1 paper)Journal of Clinical Oncology (1 paper)BMC Bioinformatics (1 paper)Genome Research (1 paper)
- Partner nations
- United StatesSpain
In The Last Decade
Shuba Gopal
10 papers receiving 419 citations
Peers
Comparison fields: 5 of 82
- Molecular Biology 346
- Aging 8
- Cancer Research 40
- Biological Psychiatry 6
- Genetics 65
Countries citing papers authored by Shuba Gopal
This map shows the geographic impact of Shuba Gopal'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 Shuba Gopal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuba Gopal more than expected).
Fields of papers citing papers by Shuba Gopal
This network shows the impact of papers produced by Shuba Gopal. 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 Shuba Gopal. The network helps show where Shuba Gopal may publish in the future.
Co-authors
The 25 scholars most cited alongside Shuba Gopal, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 143 | |
| 2 | 2001 | 104 | |
| 3 | 2012 | 78 | |
| 4 | 2001 | 43 | |
| 5 | 2005 | 21 | |
| 6 | 2017 | 14 | |
| 7 | 2006 | 12 | |
| 8 | BioInformatics: A Computing Perspective | 2008 | 8 |
| 9 | 2000 | 1 | |
| 10 | 2008 | 1 | |
| 11 | 2023 | 0 |
About Shuba Gopal
Shuba Gopal is a scholar working on Molecular Biology, Social Psychology, Sociology and Political Science, Pulmonary and Respiratory Medicine and Oncology, having authored 11 papers that have together received 425 indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (5 papers), Genomics and Phylogenetic Studies (3 papers), Advanced biosensing and bioanalysis techniques (1 paper), Machine Learning in Bioinformatics (1 paper), Genetics, Bioinformatics, and Biomedical Research (1 paper), Nutritional Studies and Diet (1 paper), Bacterial Genetics and Biotechnology (1 paper) and Nuclear Structure and Function (1 paper). The work is most often cited by research in Molecular Biology (346 citations), Aging (8 citations), Cancer Research (40 citations), Biological Psychiatry (6 citations) and Genetics (65 citations). Shuba Gopal has collaborated with scholars based in United States and Spain. Frequent co-authors include Terry Gaasterland, Monica Riley, Margrethe H. Serres, Ping Liang, Laila Alves Nahum, Clary B. Clish, Miguel Ángel Martínez‐González, Justin Scott, Amy Deik and Christine M. Albert. Their work appears in journals such as Genome biology, Nature Genetics, Journal of Clinical Oncology, BMC Bioinformatics and Genome Research.
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.