Serafim Batzoglou
- Molecular Biology top 0.5%
- Genomics and Phylogenetic Studies 47
- RNA and protein synthesis mechanisms 19
- Gene expression and cancer classification 14
- Genomics and Chromatin Dynamics 12
- Machine Learning in Bioinformatics 11
- Bioinformatics and Genomic Networks 10
- Genetics top 0.2%
- Genetic Associations and Epidemiology 9
- Cancer Research top 1%
- Aging top 2%
- Plant Science top 2%
- Chromosomal and Genetic Variations 10
- Co-authors
- Gregory M. CooperArend SidowMichael BrudnoEugene DavydovEric D. GreenMarina SirotaDavid L. GoodeR. C. Edgar
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Serafim Batzoglou
88 papers receiving 11.6k citations
Hit Papers
Peers
Comparison fields: 5 of 192
- Molecular Biology 8.9k
- Genetics 3.5k
- Cancer Research 1.2k
- Aging 111
- Plant Science 1.2k
Countries citing papers authored by Serafim Batzoglou
This map shows the geographic impact of Serafim Batzoglou'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 Serafim Batzoglou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Serafim Batzoglou more than expected).
Fields of papers citing papers by Serafim Batzoglou
This network shows the impact of papers produced by Serafim Batzoglou. 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 Serafim Batzoglou. The network helps show where Serafim Batzoglou may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Serafim Batzoglou, 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 | 2020 | 9 | |
| 2 | 2020 | 34 | |
| 3 | 2019 | 12 | |
| 4 | 2018 | 8 | |
| 5 | 2018 | 263 | |
| 6 | 2018 | 77 | |
| 7 | 2018 | 129 | |
| 8 | SIMLR: a tool for large-scale single-cell analysis by multi-kernel learning | 2017 | 3 |
| 9 | 2017 | 11 | |
| 10 | Unsupervised Learning from Noisy Networks with Applications to Hi-C Data | 2016 | 3 |
| 11 | 2015 | 8 | |
| 12 | 2015 | 133 | |
| 13 | Linking disease associations with regulatory information in the human genomebreakdown → | 2012 | 518 |
| 14 | Distribution and intensity of constraint in mammalian genomic sequencebreakdown → | 2005 | 912 |
| 15 | PROBCONS: probabilistic consistency-based multiple alignment of amino acid sequences | 2004 | 27 |
| 16 | 2004 | 105 | |
| 17 | ICA-based Clustering of Genes from Microarray Expression Data | 2003 | 5 |
| 18 | LAGAN and Multi-LAGAN: Efficient Tools for Large-Scale Multiple Alignment of Genomic DNAbreakdown → | 2003 | 876 |
| 19 | 2000 | 260 | |
| 20 | 1997 | 5 |
About Serafim Batzoglou
Serafim Batzoglou is a scholar working on Aging, Molecular Biology and Genetics, having authored 88 papers that have together received 11.8k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (47 papers), RNA and protein synthesis mechanisms (19 papers), Gene expression and cancer classification (14 papers), Genomics and Chromatin Dynamics (12 papers), Machine Learning in Bioinformatics (11 papers), Bioinformatics and Genomic Networks (10 papers), Chromosomal and Genetic Variations (10 papers) and Genetic Associations and Epidemiology (9 papers). The work is most often cited by research in Molecular Biology (8.9k citations), Genetics (3.5k citations) and Cancer Research (1.2k citations). Serafim Batzoglou has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Gregory M. Cooper, Arend Sidow, Michael Brudno, Eugene Davydov, Eric D. Green, Marina Sirota, David L. Goode, R. C. Edgar, Eric A. Stone and Arend Sidow. Their work appears in journals such as Science, Cell and Proceedings of the National Academy of Sciences.
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.