Igor Paron
- Spectroscopy top 0.5%
- Advanced Proteomics Techniques and Applications 5
- Mass Spectrometry Techniques and Applications 3
- Molecular Biology top 1%
- Glycosylation and Glycoproteins Research 3
- Mitochondrial Function and Pathology 2
- Molecular Biology Techniques and Applications 2
- Connexins and lens biology 2
- Redox biology and oxidative stress 2
- Aging top 5%
- Cell Biology top 2%
- Immunology top 5%
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- Animal Genetics and Reproduction 2
- Co-authors
- Matthias MannNagarjuna NagarajMarco Y. HeinChristian A. LuberJürgen CoxNils A. KulakGarwin PichlerGianluca Tell
- Cited by
- SpectroscopyMolecular BiologyAging
- Journals
- Molecular & Cellular Proteomics (3 papers)Human Mutation (2 papers)Cancer Letters (2 papers)
- Partner nations
- ItalyGermanyUnited States
In The Last Decade
Igor Paron
21 papers receiving 5.9k citations
Hit Papers
Peers
Comparison fields: 5 of 140
- Spectroscopy 1.3k
- Molecular Biology 4.1k
- Aging 69
- Cell Biology 642
- Immunology 596
Countries citing papers authored by Igor Paron
This map shows the geographic impact of Igor Paron'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 Igor Paron with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Igor Paron more than expected).
Fields of papers citing papers by Igor Paron
This network shows the impact of papers produced by Igor Paron. 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 Igor Paron. The network helps show where Igor Paron may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Igor Paron, 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 | 255 | |
| 2 | 2015 | 134 | |
| 3 | 2015 | 16 | |
| 4 | Minimal, encapsulated proteomic-sample processing applied to copy-number estimation in eukaryotic cellsbreakdown → | 2014 | 1227 |
| 5 | Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQbreakdown → | 2014 | 3568 |
| 6 | 2011 | 58 | |
| 7 | 2011 | 51 | |
| 8 | 2010 | 45 | |
| 9 | 2006 | 17 | |
| 10 | 2006 | 5 | |
| 11 | 2006 | 54 | |
| 12 | 2005 | 17 | |
| 13 | 2005 | 58 | |
| 14 | 2004 | 40 | |
| 15 | 2003 | 19 | |
| 16 | 2003 | 96 | |
| 17 | 2002 | 37 | |
| 18 | 2002 | 2 | |
| 19 | 2001 | 68 | |
| 20 | 2001 | 52 |
About Igor Paron
Igor Paron is a scholar working on Process Chemistry and Technology, Spectroscopy and Molecular Biology, having authored 21 papers that have together received 5.9k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (5 papers), Glycosylation and Glycoproteins Research (3 papers), Mass Spectrometry Techniques and Applications (3 papers), Mitochondrial Function and Pathology (2 papers), Molecular Biology Techniques and Applications (2 papers), Connexins and lens biology (2 papers), Animal Genetics and Reproduction (2 papers) and Redox biology and oxidative stress (2 papers). The work is most often cited by research in Spectroscopy (1.3k citations), Molecular Biology (4.1k citations) and Aging (69 citations). Igor Paron has collaborated with scholars based in Italy, Germany and United States. Frequent co-authors include Matthias Mann, Nagarjuna Nagaraj, Marco Y. Hein, Christian A. Luber, Jürgen Cox, Nils A. Kulak, Garwin Pichler, Gianluca Tell, Giuseppe Damante and Andrea Scaloni. Their work appears in journals such as Molecular & Cellular Proteomics, Human Mutation, Cancer Letters, Biochemical and Biophysical Research Communications and Nature Methods.
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.