Arvind Singh Mer

2.2k total citations
24 papers, 577 citations indexed

About

Arvind Singh Mer is a scholar working on Molecular Biology, Cancer Research and Computational Theory and Mathematics. According to data from OpenAlex, Arvind Singh Mer has authored 24 papers receiving a total of 577 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 14 papers in Cancer Research and 7 papers in Computational Theory and Mathematics. Recurrent topics in Arvind Singh Mer's work include Cancer Genomics and Diagnostics (9 papers), Computational Drug Discovery Methods (7 papers) and Bioinformatics and Genomic Networks (7 papers). Arvind Singh Mer is often cited by papers focused on Cancer Genomics and Diagnostics (9 papers), Computational Drug Discovery Methods (7 papers) and Bioinformatics and Genomic Networks (7 papers). Arvind Singh Mer collaborates with scholars based in Canada, Sweden and Germany. Arvind Singh Mer's co-authors include Benjamin Haibe‐Kains, Petr Smirnov, Ming‐Sound Tsao, Ruoshi Shi, Laura Tamblyn, Geoffrey Liu, Christer Nilsson, Michael Cabanero, Yu-Hui Wang and Ni Liu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Blood.

In The Last Decade

Arvind Singh Mer

20 papers receiving 567 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arvind Singh Mer Canada 11 311 196 182 95 71 24 577
Swapnil Potdar Finland 12 251 0.8× 100 0.5× 176 1.0× 65 0.7× 53 0.7× 40 538
Grace R. Anderson United States 11 573 1.8× 210 1.1× 190 1.0× 63 0.7× 39 0.5× 13 763
Anne Marie Mazzola United States 7 388 1.2× 145 0.7× 224 1.2× 147 1.5× 18 0.3× 11 664
Lamei Huang China 5 427 1.4× 143 0.7× 248 1.4× 113 1.2× 24 0.3× 7 677
J. Mills United Kingdom 11 253 0.8× 172 0.9× 290 1.6× 100 1.1× 48 0.7× 21 671
Grit S. Herter-Sprie United States 10 350 1.1× 137 0.7× 307 1.7× 103 1.1× 29 0.4× 14 680
Diede Brunen Netherlands 10 485 1.6× 152 0.8× 190 1.0× 69 0.7× 24 0.3× 14 700
Changyong Wei United States 12 477 1.5× 215 1.1× 145 0.8× 46 0.5× 25 0.4× 20 656
Iker Reyes-Salazar Spain 3 590 1.9× 352 1.8× 156 0.9× 142 1.5× 15 0.2× 3 856
Leanna S. Morinishi United States 4 266 0.9× 140 0.7× 148 0.8× 94 1.0× 23 0.3× 5 406

Countries citing papers authored by Arvind Singh Mer

Since Specialization
Citations

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

Fields of papers citing papers by Arvind Singh Mer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arvind Singh Mer. 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 Arvind Singh Mer. The network helps show where Arvind Singh Mer may publish in the future.

Co-authorship network of co-authors of Arvind Singh Mer

This figure shows the co-authorship network connecting the top 25 collaborators of Arvind Singh Mer. A scholar is included among the top collaborators of Arvind Singh Mer 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 Arvind Singh Mer. Arvind Singh Mer 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.
Yasavoli‐Sharahi, Hamed, et al.. (2025). Global DNA methylation signatures associated with chemoresistance and poor prognosis of high grade serous ovarian cancer. Scientific Reports. 15(1). 36869–36869.
2.
Wu, Grace C., et al.. (2024). Text-mining-based feature selection for anticancer drug response prediction. Bioinformatics Advances. 4(1). vbae047–vbae047.
3.
Yang, Yidai, Zhibin Ning, Daniel Figeys, et al.. (2024). Structural insights into an atypical histone binding mechanism by a PHD finger. Structure. 32(9). 1498–1506.e4.
4.
Mer, Arvind Singh, et al.. (2023). Large-scale phenogenomic analysis of human cancers uncovers frequent alterations affecting SMC5/6 complex components in breast cancer. NAR Cancer. 5(3). zcad047–zcad047. 5 indexed citations
5.
Audet-Delage, Yannick, Catherine St‐Louis, Lucía Minarrieta, et al.. (2023). Spatiotemporal modeling of chemoresistance evolution in breast tumors uncovers dependencies on SLC38A7 and SLC46A1. Cell Reports. 42(10). 113191–113191. 6 indexed citations
6.
Ba-Alawi, Wail, Bo Li, Petr Smirnov, et al.. (2022). Bimodal Gene Expression in Patients with Cancer Provides Interpretable Biomarkers for Drug Sensitivity. Cancer Research. 82(13). 2378–2387. 5 indexed citations
7.
Sharifi-Noghabi, Hossein, Petr Smirnov, C. Suk-Yee Hon, et al.. (2021). Drug sensitivity prediction from cell line-based pharmacogenomics data: guidelines for developing machine learning models. Briefings in Bioinformatics. 22(6). 36 indexed citations
8.
Smirnov, Petr, Minoru Nakano, Arvind Singh Mer, et al.. (2021). PharmacoDB 2.0: improving scalability and transparency of in vitro pharmacogenomics analysis. Nucleic Acids Research. 50(D1). D1348–D1357. 20 indexed citations
9.
Mer, Arvind Singh, Wail Ba-Alawi, Petr Smirnov, et al.. (2019). Integrative Pharmacogenomics Analysis of Patient-Derived Xenografts. Cancer Research. 79(17). 4539–4550. 30 indexed citations
10.
Shi, Ruoshi, Nikolina Radulovich, Christine Ng, et al.. (2019). Organoid Cultures as Preclinical Models of Non–Small Cell Lung Cancer. Clinical Cancer Research. 26(5). 1162–1174. 204 indexed citations
11.
Mer, Arvind Singh, Petr Smirnov, Ming‐Sound Tsao, et al.. (2019). Abstract 3378: Systematic pharmacogenomic analysis of large patient derived xenografts data. Cancer Research. 79(13_Supplement). 3378–3378. 1 indexed citations
12.
Mer, Arvind Singh, Johan Lindberg, Christer Nilsson, et al.. (2018). Expression levels of long non-coding RNAs are prognostic for AML outcome. Journal of Hematology & Oncology. 11(1). 52–52. 41 indexed citations
13.
Ramos, Marcel, Lucas Schiffer, Angela Re, et al.. (2017). Software for the Integration of Multiomics Experiments in Bioconductor. Cancer Research. 77(21). e39–e42. 61 indexed citations
14.
Lindberg, Johan, Daniel Klevebring, Christer Nilsson, et al.. (2017). Validation of risk stratification models in acute myeloid leukemia using sequencing-based molecular profiling. Leukemia. 31(10). 2029–2036. 46 indexed citations
15.
El-Hachem, Nehmé, Wail Ba-Alawi, Ian C. P. Smith, Arvind Singh Mer, & Benjamin Haibe‐Kains. (2017). Integrative Cancer Pharmacogenomics to Establish Drug Mechanism of Action: Drug Repurposing. Pharmacogenomics. 18(16). 1469–1472. 3 indexed citations
16.
Mer, Arvind Singh, Daniel Klevebring, Henrik Grönberg, & Mattias Rantalainen. (2016). Study design requirements for RNA sequencing-based breast cancer diagnostics. Scientific Reports. 6(1). 20200–20200. 1 indexed citations
17.
Mer, Arvind Singh, et al.. (2015). mBISON: Finding miRNA target over-representation in gene lists from ChIP-sequencing data. BMC Research Notes. 8(1). 157–157. 2 indexed citations
18.
Malatras, Apostolos, Arvind Singh Mer, Stéphanie Duguez, et al.. (2015). CellWhere: graphical display of interaction networks organized on subcellular localizations. Nucleic Acids Research. 43(W1). W571–W575. 17 indexed citations
19.
Mer, Arvind Singh & Miguel A. Andrade‐Navarro. (2013). A novel approach for protein subcellular location prediction using amino acid exposure. BMC Bioinformatics. 14(1). 342–342. 10 indexed citations
20.
Vaz, Candida, Arvind Singh Mer, Alok Bhattacharya, & Ramakrishna Ramaswamy. (2011). MicroRNAs Modulate the Dynamics of the NF-κB Signaling Pathway. PLoS ONE. 6(11). e27774–e27774. 14 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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