The rise of deep learning in drug discovery2018 · 1.1k citations
What are hit papers?
Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if any of the following hold:
it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the
threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.
Countries citing papers authored by Marcus Olivecrona
Since Specialization
Citations
This map shows the geographic impact of Marcus Olivecrona'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 Marcus Olivecrona with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcus Olivecrona more than expected).
Fields of papers citing papers by Marcus Olivecrona
This network shows the impact of papers produced by Marcus Olivecrona. 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 Marcus Olivecrona. The network helps show where Marcus Olivecrona may publish in the future.
Co-authors
The 5 scholars most cited alongside Marcus Olivecrona, linked wherever they
have co-authored with each other. Click a name or a connecting line to browse the papers
they share.
Border = papers with Marcus OlivecronaLine = papers co-authored togetherMarcus Olivecrona links everyone, so they are left out of the graph.
Marcus Olivecrona is a scholar working on Materials Chemistry, Molecular Biology, Computational Theory and Mathematics, Artificial Intelligence and Mechanical Engineering, having authored 3 papers that have together received 2.1k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (3 papers), Computational Drug Discovery Methods (2 papers), Genetics, Bioinformatics, and Biomedical Research (1 paper), Modular Robots and Swarm Intelligence (1 paper), Evolutionary Algorithms and Applications (1 paper) and Protein Structure and Dynamics (1 paper). The work is most often cited by research in Computational Theory and Mathematics (1.5k citations), Health Informatics (48 citations), Materials Chemistry (980 citations), Biophysics (109 citations) and Molecular Biology (1.1k citations). Marcus Olivecrona has collaborated with scholars based in Sweden, Germany and United Kingdom. Frequent co-authors include Thomas Blaschke, Ola Engkvist, Hongming Chen, Yinhai Wang and Jürgen Bajorath. Their work appears in journals such as Journal of Cheminformatics, Molecular Informatics and Drug Discovery Today.
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.