Akanksha Arora

404 total citations · 1 hit paper
11 papers, 144 citations indexed

About

Akanksha Arora is a scholar working on Molecular Biology, Microbiology and Cancer Research. According to data from OpenAlex, Akanksha Arora has authored 11 papers receiving a total of 144 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Microbiology and 3 papers in Cancer Research. Recurrent topics in Akanksha Arora's work include Machine Learning in Bioinformatics (3 papers), Extracellular vesicles in disease (2 papers) and Cancer-related molecular mechanisms research (2 papers). Akanksha Arora is often cited by papers focused on Machine Learning in Bioinformatics (3 papers), Extracellular vesicles in disease (2 papers) and Cancer-related molecular mechanisms research (2 papers). Akanksha Arora collaborates with scholars based in India, South Korea and United States. Akanksha Arora's co-authors include Gajendra P. S. Raghava, Shubham Choudhury, Sumeet Patiyal, Anjali Dhall, Dilraj Kaur, Liying Zhang, Neelam Sharma, Shivendra Shivani, Sung Hoon Kim and David Chia and has published in prestigious journals such as Scientific Reports, Frontiers in Microbiology and PROTEOMICS.

In The Last Decade

Akanksha Arora

10 papers receiving 143 citations

Hit Papers

ToxinPred 3.0: An improved method for predicting the toxi... 2024 2026 2025 2024 25 50 75
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. ToxinPred 3.0: An improved method for predicting the toxicity of peptides
    2024 78 citations Shubham Choudhury, Akanksha Arora et al. Computers in Biology and Medicine profile →

Peers

Akanksha Arora
Johan Teleman Sweden
Moritz Herrmann Germany
Victor Reys France
Roye Rozov Israel
Lulu Zheng China
Dimitri Guala Sweden
Hsuan-Lin Her United States
Stefanie Kaufmann Germany
Johan Teleman Sweden
Akanksha Arora
Citations per year, relative to Akanksha Arora Akanksha Arora (= 1×) peers Johan Teleman

Countries citing papers authored by Akanksha Arora

Since Specialization
Citations

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

Fields of papers citing papers by Akanksha Arora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Akanksha Arora

This figure shows the co-authorship network connecting the top 25 collaborators of Akanksha Arora. A scholar is included among the top collaborators of Akanksha Arora 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 Akanksha Arora. Akanksha Arora is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
Arora, Akanksha & Gajendra P. S. Raghava. (2025). Prediction of exosomal miRNA-based biomarkers for liquid biopsy. Scientific Reports. 15(1). 31191–31191.
2.
Choudhury, Shubham, et al.. (2024). ToxinPred 3.0: An improved method for predicting the toxicity of peptides. Computers in Biology and Medicine. 179. 108926–108926. 78 indexed citations breakdown →
3.
Arora, Akanksha, et al.. (2024). Prediction of peptide hormones using an ensemble of machine learning and similarity‐based methods. PROTEOMICS. 24(20). e2400004–e2400004. 7 indexed citations
4.
Dhall, Anjali, et al.. (2024). A deep learning method for classification of HNSCC and HPV patients using single-cell transcriptomics. Frontiers in Molecular Biosciences. 11. 1395721–1395721. 2 indexed citations
5.
Arora, Akanksha, et al.. (2023). SalivaDB—a comprehensive database for salivary biomarkers in humans. Database. 2023. 9 indexed citations
6.
Arora, Akanksha, et al.. (2023). A random forest model for predicting exosomal proteins using evolutionary information and motifs. PROTEOMICS. 24(6). e2300231–e2300231. 8 indexed citations
7.
Arora, Akanksha, et al.. (2023). Hmrbase2: a comprehensive database of hormones and their receptors. HORMONES. 22(3). 359–366. 4 indexed citations
8.
Cheng, Jordan, You Jeong Heo, Akanksha Arora, et al.. (2023). Multi-faceted attributes of salivary cell-free DNA as liquid biopsy biomarkers for gastric cancer detection. Biomarker Research. 11(1). 90–90. 10 indexed citations
9.
Dhall, Anjali, et al.. (2023). An ensemble method for prediction of phage-based therapy against bacterial infections. Frontiers in Microbiology. 14. 1148579–1148579. 19 indexed citations
10.
Aggarwal, Bhawna, et al.. (2023). A Floating Decremental/ Incremental Meminductor Emulator Using Voltage Differencing Inverted Buffered Amplifier and Current Follower. Journal of Circuits Systems and Computers. 32(14). 5 indexed citations
11.
Arora, Akanksha, Hitendra Garg, & Shivendra Shivani. (2022). Anti-phishing technique based on dynamic image captcha using multi secret sharing scheme. Journal of Visual Communication and Image Representation. 88. 103624–103624. 2 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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