Claudio Lottaz
Impact in
- Immunology top 5%
- Immune cells in cancer
- Cancer Research top 5%
- Cancer Genomics and Diagnostics
Papers in
-
- Gene expression and cancer classification 6
- Genomics and Phylogenetic Studies 5
- RNA and protein synthesis mechanisms 4
- Bioinformatics and Genomic Networks 4
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- AI-based Problem Solving and Planning 3
- Co-authors
- Heinz Himmelbauer (2 shared papers)Tatiana Borodina (2 shared papers)Juliane C. Dohm (2 shared papers)Rainer Spang (12 shared papers)Reinhard Hoffmann (3 shared papers)Muzlifah Haniffa (2 shared papers)Frank Tacke (2 shared papers)Emmanuel L. Gautier (2 shared papers)
- Journals
- Bioinformatics (4 papers)Blood (3 papers)BMC Bioinformatics (3 papers)Leukemia (3 papers)Clinical Cancer Research (1 paper)
- Partner nations
- GermanySwitzerlandUnited States
In The Last Decade
Claudio Lottaz
31 papers receiving 2.9k citations
Claudio Lottaz's Hit Papers
Peers
Comparison fields: 5 of 150
- Immunology 658
- Cancer Research 435
- Hematology 264
- Molecular Biology 1.6k
- Genetics 216
Countries citing papers authored by Claudio Lottaz
This map shows the geographic impact of Claudio Lottaz'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 Claudio Lottaz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Claudio Lottaz more than expected).
Fields of papers citing papers by Claudio Lottaz
This network shows the impact of papers produced by Claudio Lottaz. 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 Claudio Lottaz. The network helps show where Claudio Lottaz may publish in the future.
Co-authors
The 25 scholars most cited alongside Claudio Lottaz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Substantial biases in ultra-short read data sets from high-throughput DNA sequencing Hit paper breakdown → | 2008 | 796 |
| 2 | Comparison of gene expression profiles between human and mouse monocyte subsets Hit paper breakdown → | 2009 | 536 |
| 3 | 2012 | 326 | |
| 4 | 2010 | 207 | |
| 5 | 2007 | 180 | |
| 6 | 2012 | 112 | |
| 7 | 2003 | 104 | |
| 8 | 2007 | 85 | |
| 9 | 2004 | 84 | |
| 10 | 2013 | 73 | |
| 11 | 2012 | 58 | |
| 12 | 2006 | 55 | |
| 13 | 1999 | 43 | |
| 14 | 2009 | 40 | |
| 15 | 2000 | 40 | |
| 16 | 2014 | 34 | |
| 17 | 2006 | 32 | |
| 18 | 2011 | 32 | |
| 19 | 2005 | 31 | |
| 20 | 2019 | 28 |
About Claudio Lottaz
Claudio Lottaz is a scholar working on Molecular Biology, Artificial Intelligence, Computer Networks and Communications, Immunology and Cancer Research, having authored 33 papers that have together received 3.0k indexed citations. Recurring topics across this work include Gene expression and cancer classification (6 papers), Genomics and Phylogenetic Studies (5 papers), Constraint Satisfaction and Optimization (5 papers), Immune Cell Function and Interaction (4 papers), RNA and protein synthesis mechanisms (4 papers), Bioinformatics and Genomic Networks (4 papers), Data Management and Algorithms (3 papers) and AI-based Problem Solving and Planning (3 papers). The work is most often cited by research in Immunology (658 citations), Cancer Research (435 citations), Hematology (264 citations), Molecular Biology (1.6k citations) and Genetics (216 citations). Claudio Lottaz has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Heinz Himmelbauer, Tatiana Borodina, Juliane C. Dohm, Rainer Spang, Reinhard Hoffmann, Muzlifah Haniffa, Frank Tacke, Emmanuel L. Gautier, Gwendalyn J. Randolph and Marion Frankenberger. Their work appears in journals such as Bioinformatics, Blood, BMC Bioinformatics, Leukemia and Clinical Cancer 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.