Disha Malani

1.5k citations
15 papers · 531 · h-index 9

Impact in

Papers in

    • Acute Myeloid Leukemia Research 8
    • Chronic Myeloid Leukemia Treatments 3
    • Multiple Myeloma Research and Treatments 3
    • Bioinformatics and Genomic Networks 3
    • Protein Degradation and Inhibitors 2

Disha Malani

14 papers receiving 525 citations

Peers

Disha Malani
Comparison fields: 5 of 64
  • Hematology 160
  • Computational Theory and Mathematics 123
  • Cancer Research 101
  • Genetics 71
  • Biophysics 34
Replace Tea Pemovska with:
Tea Pemovska Finland
Swapnil Potdar Finland
Mika Kontro Finland
In Sock Jang United States
Erik Koenig United States
Krysta Schlis United States
Rada Amin United States
Aleksandra Wroblewska Netherlands
Orsi Giricz United States
Bhairavi Tolani United States
Disha Malani relative to Tea Pemovska Finland Tea Pemovska's profile →
Citations per field
00.5×1.5×
Tea Pemovska · 1×
Citations per year

Countries citing papers authored by Disha Malani

Since Specialization
Citations

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

Fields of papers citing papers by Disha Malani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Disha Malani, 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 Disha Malani Line = papers co-authored together Disha Malani links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 2014214
2 201681
3 201666
4 201656
5 201644
6 201919
7 201617
8 202116
9 20219
10 20243
11 20203
12 20241
13 20171
14 20191
15 20250

About Disha Malani

Disha Malani is a scholar working on Hematology, Molecular Biology, Oncology, Computational Theory and Mathematics and Genetics, having authored 15 papers that have together received 531 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (8 papers), Computational Drug Discovery Methods (4 papers), Cancer Genomics and Diagnostics (3 papers), Chronic Myeloid Leukemia Treatments (3 papers), Bioinformatics and Genomic Networks (3 papers), Multiple Myeloma Research and Treatments (3 papers), Protein Degradation and Inhibitors (2 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (2 papers). The work is most often cited by research in Hematology (160 citations), Computational Theory and Mathematics (123 citations), Cancer Research (101 citations), Genetics (71 citations) and Biophysics (34 citations). Disha Malani has collaborated with scholars based in Finland, Sweden and Norway. Frequent co-authors include Olli Kallioniemi, Tero Aittokallio, Astrid Murumägi, Krister Wennerberg, Bhagwan Yadav, Caroline A. Heckman, Kimmo Porkka, Mika Kontro, Tea Pemovska and Muntasir Mamun Majumder. Their work appears in journals such as Blood, Scientific Reports, Leukemia, Cell Death and Disease and Oncotarget.

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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