Ayse Batova

28 papers receiving 1.1k citations

Peers

Ayse Batova
Comparison fields: 5 of 78
  • Neurology 193
  • Cancer Research 158
  • Oncology 213
  • Toxicology 28
  • Molecular Biology 574
Replace Smita S. Matkar with:
Smita S. Matkar United States
Andrew J. Olaharski United States
Gilles Despouy France
Hans‐Ulrich Naegeli Switzerland
Marie-Christine Bissery France
Qipan Deng China
Sanae Matsumoto Japan
Marina Fernanda Vita Sweden
Lih‐Ching Hsu Taiwan
Joana Soares Portugal
Ayse Batova relative to Smita S. Matkar United States Smita S. Matkar's profile →
Citations per field
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Smita S. Matkar · 1×
Citations per year

Countries citing papers authored by Ayse Batova

Since Specialization
Citations

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

Fields of papers citing papers by Ayse Batova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021162
2
Frequent and selective methylation of p15 and deletion of both p15 and p16 in T-cell acute lymphoblastic leukemia.
1997144
3 2010121
4 200264
5 200953
6 199542
7 201441
8 200639
9 199736
10 201336
11
Retinoic acid induces secretion of latent transforming growth factor beta 1 and beta 2 in normal and human papillomavirus type 16-immortalized human keratinocytes.
199235
12 199933
13 201731
14 200029
15 201228
16 201224
17 199623
18 201023
19 199418
20 201118

About Ayse Batova

Ayse Batova is a scholar working on Cancer Research, Neurology, Molecular Biology, Plant Science and Oncology, having authored 28 papers that have together received 1.1k indexed citations. Recurring topics across this work include Natural Compound Pharmacology Studies (8 papers), Neuroblastoma Research and Treatments (6 papers), Retinoids in leukemia and cellular processes (6 papers), Cancer-related Molecular Pathways (5 papers), Biological Activity of Diterpenoids and Biflavonoids (4 papers), Epigenetics and DNA Methylation (4 papers), Cancer, Hypoxia, and Metabolism (4 papers) and Carbohydrate Chemistry and Synthesis (4 papers). The work is most often cited by research in Neurology (193 citations), Cancer Research (158 citations), Oncology (213 citations), Toxicology (28 citations) and Molecular Biology (574 citations). Ayse Batova has collaborated with scholars based in United States, Taiwan and Thailand. Frequent co-authors include Alice Lin-Tsing Yu, Mitchell B. Diccianni, Emmanuel A. Theodorakis, Oraphin Chantarasriwong, John C. L. Yu, Warinthorn Chavasiri, Kim E. Creek, Lucia A. Pirisi, Jeanette Pullen and Tsutomu Nobori. Their work appears in journals such as Organic & Biomolecular Chemistry, Chemistry - A European Journal, Blood, Advances in experimental medicine and biology and International Journal of Cancer.

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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