Žiga Avsec
Impact in
- Molecular Biology top 5%
- RNA and protein synthesis mechanisms
- Genomics and Chromatin Dynamics
- Single-cell and spatial transcriptomics
- Genomics and Phylogenetic Studies
- RNA Research and Splicing
- RNA modifications and cancer
- Machine Learning in Bioinformatics
- Biophysics top 2%
Papers in
-
- RNA and protein synthesis mechanisms 8
- RNA Research and Splicing 6
- RNA modifications and cancer 5
- Genomics and Chromatin Dynamics 5
- Genomics and Phylogenetic Studies 2
- Co-authors
- Julien GagneurFabian J. TheisGökçen EraslanPushmeet KohliJohn JumperJun ChengDaniel VisentinAgnieszka Grabska‐Barwińska
- Journals
- Nature Methods (1 paper)The American Journal of Human Genetics (1 paper)Nature Genetics (1 paper)PLoS Computational Biology (1 paper)Human Mutation (1 paper)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Žiga Avsec
14 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 156
- Molecular Biology 2.1k
- Biophysics 147
- Health Informatics 32
- Genetics 616
- Cancer Research 290
Countries citing papers authored by Žiga Avsec
This map shows the geographic impact of Žiga Avsec'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 Žiga Avsec with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Žiga Avsec more than expected).
Fields of papers citing papers by Žiga Avsec
This network shows the impact of papers produced by Žiga Avsec. 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 Žiga Avsec. The network helps show where Žiga Avsec may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Žiga Avsec, 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 | 2023 | 3 | |
| 2 | Accurate proteome-wide missense variant effect prediction with AlphaMissense Hit paper breakdown → | 2023 | 692 |
| 3 | 2023 | 1 | |
| 4 | 2021 | 23 | |
| 5 | Effective gene expression prediction from sequence by integrating long-range interactions Hit paper breakdown → | 2021 | 486 |
| 6 | Mapping single-cell data to reference atlases by transfer learning Hit paper breakdown → | 2021 | 247 |
| 7 | Base-resolution models of transcription-factor binding reveal soft motif syntax Hit paper breakdown → | 2021 | 294 |
| 8 | Deep learning: new computational modelling techniques for genomics Hit paper breakdown → | 2019 | 715 |
| 9 | 2019 | 125 | |
| 10 | 2019 | 7 | |
| 11 | TF-MoDISco v0.4.2.2-alpha: Technical Note | 2018 | 8 |
| 12 | 2018 | 99 | |
| 13 | 2017 | 20 | |
| 14 | 2017 | 44 |
About Žiga Avsec
Žiga Avsec is a scholar working on Biophysics, Molecular Biology, Genetics, Cancer Research and Immunology, having authored 14 papers that have together received 2.8k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (8 papers), RNA Research and Splicing (6 papers), RNA modifications and cancer (5 papers), Genomics and Chromatin Dynamics (5 papers), Genomics and Rare Diseases (2 papers), Genetic Associations and Epidemiology (2 papers), Genomics and Phylogenetic Studies (2 papers) and Genomic variations and chromosomal abnormalities (1 paper). The work is most often cited by research in Molecular Biology (2.1k citations), Biophysics (147 citations), Health Informatics (32 citations), Genetics (616 citations) and Cancer Research (290 citations). Žiga Avsec has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Julien Gagneur, Fabian J. Theis, Gökçen Eraslan, Pushmeet Kohli, John Jumper, Jun Cheng, Daniel Visentin, Agnieszka Grabska‐Barwińska, Vikram Agarwal and Yannis Assael. Their work appears in journals such as Nature Methods, The American Journal of Human Genetics, Nature Genetics, PLoS Computational Biology and Human Mutation.
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.