Klev Diamanti

14.9k total citations
20 papers, 224 citations indexed

About

Klev Diamanti is a scholar working on Molecular Biology, Genetics and Epidemiology. According to data from OpenAlex, Klev Diamanti has authored 20 papers receiving a total of 224 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 4 papers in Genetics and 3 papers in Epidemiology. Recurrent topics in Klev Diamanti's work include Bioinformatics and Genomic Networks (4 papers), RNA modifications and cancer (4 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). Klev Diamanti is often cited by papers focused on Bioinformatics and Genomic Networks (4 papers), RNA modifications and cancer (4 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). Klev Diamanti collaborates with scholars based in Sweden, Poland and United States. Klev Diamanti's co-authors include Jan Komorowski, Marco Cavalli, Claes Wadelius, Gang Pan, Chanchal Kumar, Michał J. Dąbrowski, Husen M. Umer, Maria J. Pereira, Jan W. Eriksson and Stanko Skrtic and has published in prestigious journals such as Nucleic Acids Research, Scientific Reports and The Plant Journal.

In The Last Decade

Klev Diamanti

19 papers receiving 221 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Klev Diamanti Sweden 9 144 34 31 28 27 20 224
Yuping Xu China 6 137 1.0× 36 1.1× 22 0.7× 31 1.1× 32 1.2× 13 286
Lena Hansson United Kingdom 5 228 1.6× 34 1.0× 15 0.5× 24 0.9× 20 0.7× 7 281
Chunyan Luo China 11 149 1.0× 42 1.2× 55 1.8× 14 0.5× 39 1.4× 17 271
Yoshiko Mukumoto Japan 7 170 1.2× 40 1.2× 44 1.4× 37 1.3× 22 0.8× 7 289
Melissa H. Chang Australia 11 118 0.8× 40 1.2× 22 0.7× 42 1.5× 14 0.5× 21 293
Allyson L. Toro United States 13 235 1.6× 51 1.5× 30 1.0× 41 1.5× 11 0.4× 29 355
Marie Elebring Sweden 10 139 1.0× 49 1.4× 22 0.7× 15 0.5× 13 0.5× 13 255
Jane A. Dymott United Kingdom 6 193 1.3× 87 2.6× 29 0.9× 33 1.2× 18 0.7× 6 329
Natsuko Ohtomo Japan 8 180 1.3× 21 0.6× 52 1.7× 28 1.0× 9 0.3× 12 271
Bochra Tourki United States 10 132 0.9× 15 0.4× 25 0.8× 50 1.8× 24 0.9× 15 296

Countries citing papers authored by Klev Diamanti

Since Specialization
Citations

This map shows the geographic impact of Klev Diamanti'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 Klev Diamanti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Klev Diamanti more than expected).

Fields of papers citing papers by Klev Diamanti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Klev Diamanti. 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 Klev Diamanti. The network helps show where Klev Diamanti may publish in the future.

Co-authorship network of co-authors of Klev Diamanti

This figure shows the co-authorship network connecting the top 25 collaborators of Klev Diamanti. A scholar is included among the top collaborators of Klev Diamanti based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Klev Diamanti. Klev Diamanti is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Diamanti, Klev, Louella Vasquez, Paul Theodor Pyl, et al.. (2025). Combinatorial DNMTs and EZH2 inhibition reprograms the H3K27me3 and DNAme-mediated onco-epigenome to suppress multiple myeloma proliferation. Scientific Reports. 15(1). 31568–31568. 2 indexed citations
2.
Diamanti, Klev, et al.. (2022). Interpretable machine learning identifies paediatric Systemic Lupus Erythematosus subtypes based on gene expression data. Scientific Reports. 12(1). 7433–7433. 8 indexed citations
3.
Barrenäs, Fredrik, et al.. (2022). Machine Learning-Based Analysis of Glioma Grades Reveals Co-Enrichment. Cancers. 14(4). 1014–1014. 3 indexed citations
4.
Diamanti, Klev, Marco Cavalli, Maria J. Pereira, et al.. (2022). Organ-specific metabolic pathways distinguish prediabetes, type 2 diabetes, and normal tissues. Cell Reports Medicine. 3(10). 100763–100763. 21 indexed citations
5.
Cavalli, Marco, Klev Diamanti, Yonglong Dang, et al.. (2021). The Thioesterase ACOT1 as a Regulator of Lipid Metabolism in Type 2 Diabetes Detected in a Multi-Omics Study of Human Liver. OMICS A Journal of Integrative Biology. 25(10). 652–659. 9 indexed citations
6.
Diamanti, Klev, et al.. (2021). R.ROSETTA: an interpretable machine learning framework. BMC Bioinformatics. 22(1). 110–110. 15 indexed citations
7.
Komorowski, Jan, et al.. (2021). MetaFetcheR: An R Package for Complete Mapping of Small-Compound Data. Metabolites. 11(11). 743–743.
8.
Cavalli, Marco, Klev Diamanti, Gang Pan, et al.. (2021). A non-coding cancer mutation disrupting an HNF4α binding motif affects an enhancer regulating genes associated to the progression of liver cancer. Experimental Oncology. 43(1). 2–6. 1 indexed citations
9.
Diamanti, Klev, et al.. (2021). Interpretable Machine Learning Reveals Dissimilarities Between Subtypes of Autism Spectrum Disorder. Frontiers in Genetics. 12. 618277–618277. 6 indexed citations
10.
Pan, Gang, et al.. (2021). Multifaceted regulation of hepatic lipid metabolism by YY1. Life Science Alliance. 4(7). e202000928–e202000928. 20 indexed citations
11.
Diamanti, Klev, Marco Cavalli, Maria J. Pereira, et al.. (2021). Organ-Specific Metabolic Pathways Distinguish Prediabetes, Type 2 Diabetes and Normal Tissues. SSRN Electronic Journal. 2 indexed citations
12.
Cavalli, Marco, Klev Diamanti, Gang Pan, et al.. (2020). A Multi-Omics Approach to Liver Diseases: Integration of Single Nuclei Transcriptomics with Proteomics and HiCap Bulk Data in Human Liver. OMICS A Journal of Integrative Biology. 24(4). 180–194. 26 indexed citations
13.
Diamanti, Klev, Maria J. Pereira, Marco Cavalli, et al.. (2020). Integration of whole-body [18F]FDG PET/MRI with non-targeted metabolomics can provide new insights on tissue-specific insulin resistance in type 2 diabetes. Scientific Reports. 10(1). 8343–8343. 8 indexed citations
14.
Diamanti, Klev, et al.. (2020). Single nucleus transcriptomics data integration recapitulates the major cell types in human liver. Hepatology Research. 51(2). 233–238. 9 indexed citations
15.
Diamanti, Klev, et al.. (2020). Nucleolar rDNA folds into condensed foci with a specific combination of epigenetic marks. The Plant Journal. 105(6). 1534–1548. 5 indexed citations
16.
Diamanti, Klev, Marco Cavalli, Gang Pan, et al.. (2019). Intra- and inter-individual metabolic profiling highlights carnitine and lysophosphatidylcholine pathways as key molecular defects in type 2 diabetes. Scientific Reports. 9(1). 9653–9653. 32 indexed citations
17.
Dąbrowski, Michał J., Michał Dramiński, Klev Diamanti, et al.. (2018). Unveiling new interdependencies between significant DNA methylation sites, gene expression profiles and glioma patients survival. Scientific Reports. 8(1). 4390–4390. 11 indexed citations
18.
Diamanti, Klev, Husen M. Umer, Michał J. Dąbrowski, et al.. (2016). Maps of context-dependent putative regulatory regions and genomic signal interactions. Nucleic Acids Research. 44(19). gkw800–gkw800. 8 indexed citations
19.
Umer, Husen M., Marco Cavalli, Michał J. Dąbrowski, et al.. (2016). A Significant Regulatory Mutation Burden at a High-Affinity Position of the CTCF Motif in Gastrointestinal Cancers. Human Mutation. 37(9). 904–913. 35 indexed citations
20.
Diamanti, Klev, et al.. (2014). Handling Weighted Sequences Employing Inverted Files and Suffix Trees. 231–238. 3 indexed citations

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.

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