Robert Vaser
Impact in
- Endocrinology top 5%
- Molecular Medicine top 5%
- Antibiotic Resistance in Bacteria
Papers in
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- Genomics and Phylogenetic Studies 8
- RNA and protein synthesis mechanisms 4
- Glycosylation and Glycoproteins Research 2
- Plant biochemistry and biosynthesis 1
- Plant Gene Expression Analysis 1
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- Algorithms and Data Compression 3
- Co-authors
- Mile Šikić (10 shared papers)Niranjan Nagarajan (3 shared papers)Ivan Sović (2 shared papers)Pauline C. Ng (1 shared paper)Swarnaseetha Adusumalli (1 shared paper)Cedric Chuan Young Ng (1 shared paper)Wei Liu (1 shared paper)Wing‐Kin Sung (1 shared paper)
In The Last Decade
Robert Vaser
10 papers receiving 3.0k citations
Robert Vaser's Hit Papers
Peers
Comparison fields: 5 of 135
- Endocrinology 130
- Molecular Medicine 122
- Molecular Biology 1.7k
- Horticulture 23
- Genetics 622
Countries citing papers authored by Robert Vaser
This map shows the geographic impact of Robert Vaser'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 Robert Vaser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Vaser more than expected).
Fields of papers citing papers by Robert Vaser
This network shows the impact of papers produced by Robert Vaser. 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 Robert Vaser. The network helps show where Robert Vaser may publish in the future.
Co-authors
The 15 scholars most cited alongside Robert Vaser, 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 | Fast and accurate de novo genome assembly from long uncorrected reads Hit paper breakdown → | 2017 | 1829 |
| 2 | SIFT missense predictions for genomes Hit paper breakdown → | 2015 | 913 |
| 3 | Time- and memory-efficient genome assembly with Raven Hit paper breakdown → | 2021 | 242 |
| 4 | 2016 | 21 | |
| 5 | 2019 | 13 | |
| 6 | 2022 | 5 | |
| 7 | Racon - Rapid consensus module for raw de novo genome assembly of long uncorrected reads | 2016 | 3 |
| 8 | 2021 | 2 | |
| 9 | Protein database search optimization based on CUDA and MPI | 2013 | 1 |
| 10 | 2021 | 1 |
About Robert Vaser
Robert Vaser is a scholar working on Molecular Biology, Artificial Intelligence, Small Animals, Ecology and Genetics, having authored 10 papers that have together received 3.0k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (8 papers), RNA and protein synthesis mechanisms (4 papers), Algorithms and Data Compression (3 papers), Glycosylation and Glycoproteins Research (2 papers), Phytochemicals and Antioxidant Activities (1 paper), Advanced Proteomics Techniques and Applications (1 paper), Plant biochemistry and biosynthesis (1 paper) and Plant Gene Expression Analysis (1 paper). The work is most often cited by research in Endocrinology (130 citations), Molecular Medicine (122 citations), Molecular Biology (1.7k citations), Horticulture (23 citations) and Genetics (622 citations). Robert Vaser has collaborated with scholars based in Croatia and Singapore. Frequent co-authors include Mile Šikić, Niranjan Nagarajan, Ivan Sović, Pauline C. Ng, Swarnaseetha Adusumalli, Cedric Chuan Young Ng, Wei Liu, Wing‐Kin Sung, Jing Han Hong and Prashant Shingate. Their work appears in journals such as Bioinformatics, Nature Protocols, Genome Research, Nature Computational Science and Communications Biology.
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.