Marco A. C. Neves
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- Computational Drug Discovery Methods 8
- Toxicology top 5%
- Bioactive Compounds and Antitumor Agents 2
- Molecular Medicine top 10%
- Antibiotic Resistance in Bacteria 3
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- Protein Structure and Dynamics 3
- RNA and protein synthesis mechanisms 2
- Chemical Synthesis and Analysis 1
- Pharmacology top 10%
- Inflammatory mediators and NSAID effects 2
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- Estrogen and related hormone effects 5
- Co-authors
- Ruben AbagyanMaxim TotrovM. L. Sá e MeloGiorgio ColomboSamuel SilvestreJoão F. S. CarvalhoMaria Manuel SilvaJorge A. R. Salvador
- Journals
- Journal of Biological Chemistry (1 paper)PLoS ONE (1 paper)The Journal of Physical Chemistry B (1 paper)
- Partner nations
- PortugalUnited StatesItaly
In The Last Decade
Marco A. C. Neves
16 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 103
- Computational Theory and Mathematics 264
- Toxicology 51
- Molecular Medicine 71
- Molecular Biology 639
- Pharmacology 75
Countries citing papers authored by Marco A. C. Neves
This map shows the geographic impact of Marco A. C. Neves'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 Marco A. C. Neves with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco A. C. Neves more than expected).
Fields of papers citing papers by Marco A. C. Neves
This network shows the impact of papers produced by Marco A. C. Neves. 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 Marco A. C. Neves. The network helps show where Marco A. C. Neves may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Marco A. C. Neves, 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 | 2015 | 9 | |
| 2 | 2014 | 109 | |
| 3 | 2013 | 69 | |
| 4 | 2012 | 268 | |
| 5 | 2012 | 72 | |
| 6 | 2012 | 231 | |
| 7 | 2012 | 3 | |
| 8 | 2010 | 1 | |
| 9 | 2010 | 63 | |
| 10 | 2010 | 21 | |
| 11 | 2010 | 78 | |
| 12 | 2009 | 34 | |
| 13 | 2009 | 36 | |
| 14 | 2008 | 43 | |
| 15 | 2008 | 8 | |
| 16 | 2007 | 25 |
About Marco A. C. Neves
Marco A. C. Neves is a scholar working on Molecular Medicine, Toxicology and Computational Theory and Mathematics, having authored 16 papers that have together received 1.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), Estrogen and related hormone effects (5 papers), Protein Structure and Dynamics (3 papers), Antibiotic Resistance in Bacteria (3 papers), Bioactive Compounds and Antitumor Agents (2 papers), Inflammatory mediators and NSAID effects (2 papers), RNA and protein synthesis mechanisms (2 papers) and Chemical Synthesis and Analysis (1 paper). The work is most often cited by research in Computational Theory and Mathematics (264 citations), Toxicology (51 citations) and Molecular Medicine (71 citations). Marco A. C. Neves has collaborated with scholars based in Portugal, United States and Italy. Frequent co-authors include Ruben Abagyan, Maxim Totrov, M. L. Sá e Melo, Giorgio Colombo, Samuel Silvestre, João F. S. Carvalho, Maria Manuel Silva, Jorge A. R. Salvador, Alcino J. Leitão and Teresa C.P. Dinis. Their work appears in journals such as Journal of Biological Chemistry, PLoS ONE and The Journal of Physical Chemistry B.
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.