Neetika Nath

815 total citations
28 papers, 563 citations indexed

About

Neetika Nath is a scholar working on Molecular Biology, Cancer Research and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Neetika Nath has authored 28 papers receiving a total of 563 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 6 papers in Cancer Research and 4 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Neetika Nath's work include Computational Drug Discovery Methods (4 papers), Protein Structure and Dynamics (2 papers) and DNA Repair Mechanisms (2 papers). Neetika Nath is often cited by papers focused on Computational Drug Discovery Methods (4 papers), Protein Structure and Dynamics (2 papers) and DNA Repair Mechanisms (2 papers). Neetika Nath collaborates with scholars based in Germany, United Kingdom and United States. Neetika Nath's co-authors include John B. O. Mitchell, Lars Kaderali, Ekaterina Shelest, Thomas Wolf, Marcus Vollmer, James L. McDonagh, Tanja van Mourik, Gustavo Caetano‐Anollés, Lazaros Mavridis and Andreas W. Kuß and has published in prestigious journals such as Bioinformatics, PLoS ONE and International Journal of Molecular Sciences.

In The Last Decade

Neetika Nath

27 papers receiving 554 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Neetika Nath Germany 13 241 107 84 72 65 28 563
Jun-Ichi Goto Japan 14 460 1.9× 40 0.4× 22 0.3× 38 0.5× 39 0.6× 39 866
Min Huang China 18 445 1.8× 25 0.2× 126 1.5× 41 0.6× 55 0.8× 92 1.0k
Wanida Ittarat Thailand 15 326 1.4× 183 1.7× 59 0.7× 28 0.4× 38 0.6× 24 774
Yongchao Luo China 14 581 2.4× 21 0.2× 102 1.2× 13 0.2× 58 0.9× 26 856
Minjie Mou China 14 664 2.8× 23 0.2× 123 1.5× 17 0.2× 72 1.1× 30 941
Qiansen Zhang China 18 484 2.0× 122 1.1× 30 0.4× 50 0.7× 16 0.2× 43 799
Ruifeng Hu China 19 539 2.2× 13 0.1× 142 1.7× 28 0.4× 15 0.2× 44 799
Teresa Maria Creanza Italy 12 290 1.2× 21 0.2× 82 1.0× 35 0.5× 16 0.2× 21 495
Hongjian Jiang United States 17 210 0.9× 14 0.1× 32 0.4× 35 0.5× 13 0.2× 28 891
Wei Zhuo China 16 473 2.0× 35 0.3× 59 0.7× 20 0.3× 27 0.4× 25 746

Countries citing papers authored by Neetika Nath

Since Specialization
Citations

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

Fields of papers citing papers by Neetika Nath

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Neetika Nath

This figure shows the co-authorship network connecting the top 25 collaborators of Neetika Nath. A scholar is included among the top collaborators of Neetika Nath 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 Neetika Nath. Neetika Nath 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.
Oldenburg, Jan, et al.. (2025). Explainable AI Model Reveals Informative Mutational Signatures for Cancer-Type Classification. Cancers. 17(11). 1731–1731.
2.
Köhler, Christian, Jacqueline King, Anne Pohlmann, et al.. (2023). Neighbourhood watch: genomic epidemiology of SARS-CoV-2 variants circulating in a German federal state, Mecklenburg-Western Pomerania, in 2020–2022. Emerging Microbes & Infections. 12(2). 2245916–2245916. 2 indexed citations
3.
Nath, Neetika, Cassandra Falckenhayn, Thomas C. G. Bosch, et al.. (2022). Macrophages Are Polarized toward an Inflammatory Phenotype by their Aged Microenvironment in the Human Skin. Journal of Investigative Dermatology. 142(12). 3136–3145.e11. 23 indexed citations
4.
Becker, Ann‐Kristin, Till Ittermann, Marcus Dörr, et al.. (2022). Analysis of epidemiological association patterns of serum thyrotropin by combining random forests and Bayesian networks. PLoS ONE. 17(7). e0271610–e0271610. 1 indexed citations
5.
Nath, Neetika & Stefan Simm. (2022). Machine Learning Based Methods and Best Practices of microRNA-Target Prediction and Validation. Advances in experimental medicine and biology. 1385. 109–131. 3 indexed citations
6.
Artelt, Nadine, Neetika Nath, Andreas W. Kuß, et al.. (2022). The ShGlomAssay Combines High-Throughput Drug Screening With Downstream Analyses and Reveals the Protective Role of Vitamin D3 and Calcipotriol on Podocytes. Frontiers in Cell and Developmental Biology. 10. 838086–838086. 4 indexed citations
7.
Metzendorf, Christoph, Stephan Singer, Neetika Nath, et al.. (2021). Hormonally Induced Hepatocellular Carcinoma in Diabetic Wild Type and Carbohydrate Responsive Element Binding Protein Knockout Mice. Cells. 10(10). 2787–2787. 4 indexed citations
8.
Nath, Neetika, Stefan Weiß, Ana Tzvetkova, et al.. (2020). Genome-Wide DNA Alterations in X-Irradiated Human Gingiva Fibroblasts. International Journal of Molecular Sciences. 21(16). 5778–5778. 2 indexed citations
9.
Nath, Neetika, et al.. (2020). Machine Learning-Based Solar Power Energy Forecasting. 4(3). 307–322. 3 indexed citations
10.
Köhler, Günter, Marcus Vollmer, Neetika Nath, et al.. (2019). Benign uterine mass—discrimination from leiomyosarcoma by a preoperative risk score: a multicenter cohort study. Archives of Gynecology and Obstetrics. 300(6). 1719–1727. 22 indexed citations
11.
Nath, Neetika, Lars R. Jensen, Matthias Port, et al.. (2018). Exome Sequencing Discloses Ionizing-radiation-induced DNA Variants in the Genome of Human Gingiva Fibroblasts. Health Physics. 115(1). 151–160. 3 indexed citations
12.
Endlich, Nicole, Ahmed M. Kotb, Florian Siegerist, et al.. (2018). BDNF: mRNA expression in urine cells of patients with chronic kidney disease and its role in kidney function. Journal of Cellular and Molecular Medicine. 22(11). 5265–5277. 33 indexed citations
13.
Vollmer, Marcus, et al.. (2018). A convolutional neural network for ECG annotation as the basis for classification of cardiac rhythms. Physiological Measurement. 39(10). 104005–104005. 71 indexed citations
14.
Rath, Matthias, Stefanie Spiegler, Neetika Nath, et al.. (2016). Constitutional de novo and postzygotic mutations in isolated cases of cerebral cavernous malformations. Molecular Genetics & Genomic Medicine. 5(1). 21–27. 4 indexed citations
15.
Nath, Neetika, John B. O. Mitchell, & Gustavo Caetano‐Anollés. (2014). The Natural History of Biocatalytic Mechanisms. PLoS Computational Biology. 10(5). e1003642–e1003642. 28 indexed citations
16.
McDonagh, James L., et al.. (2014). Uniting Cheminformatics and Chemical Theory To Predict the Intrinsic Aqueous Solubility of Crystalline Druglike Molecules. Journal of Chemical Information and Modeling. 54(3). 844–856. 73 indexed citations
17.
Mavridis, Lazaros, Neetika Nath, & John B. O. Mitchell. (2013). PFClust: a novel parameter free clustering algorithm. BMC Bioinformatics. 14(1). 213–213. 14 indexed citations
18.
Mavridis, Lazaros, et al.. (2012). Enzyme Informatics. Current Topics in Medicinal Chemistry. 12(17). 1911–1923. 16 indexed citations
19.
Nath, Neetika & John B. O. Mitchell. (2012). Is EC class predictable from reaction mechanism?. BMC Bioinformatics. 13(1). 60–60. 17 indexed citations
20.
Nath, Neetika, et al.. (2010). Optimizing antiangiogenic therapy for tumor minimization. 1242–1247. 6 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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