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Articles published in Journal of Data Mining in Genomics & Proteomics have been cited by esteemed scholars and scientists all around the world. Journal of Data Mining in Genomics & Proteomics has got h-index 16, which means every article in Journal of Data Mining in Genomics & Proteomics has got 16 average citations.
Following are the list of articles that have cited the articles published in Journal of Data Mining in Genomics & Proteomics.
| 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Total published articles |
30 | 56 | 30 | 30 | 23 | 2 | 4 | 8 | 30 | 22 | 23 | 34 | 14 | 4 | 5 |
Research, Review articles and Editorials |
5 | 4 | 7 | 15 | 8 | 2 | 4 | 8 | 26 | 22 | 22 | 32 | 14 | 4 | 5 |
Research communications, Review communications, Editorial communications, Case reports and Commentary |
25 | 52 | 23 | 15 | 15 | 0 | 0 | 0 | 4 | 0 | 1 | 2 | 0 | 0 | 0 |
Conference proceedings |
0 | 0 | 0 | 6 | 0 | 0 | 0 | 0 | 0 | 164 | 0 | 0 | 0 | 0 | 0 |
Citations received as per Google Scholar, other indexing platforms and portals |
86 | 104 | 118 | 125 | 166 | 142 | 170 | 190 | 150 | 77 | 52 | 46 | 11 | 14 | 0 |
| Journal total citations count | 1467 |
| Journal impact factor | 2.41 |
| Journal 5 years impact factor | 3.5 |
| Journal cite score | 7.71 |
| Journal h-index | 16 |
Important citations
Complexity and integration. A philosophical analysis of how cancer complexity can be faced in the era of precision medicine
Mou X, Jamil HM, Rinker R (2016) Visual orchestration and autonomous execution of distributed and heterogeneous computational biology pipelines. In Bioinfo Biomed 15: 752-757.
Yazdani A, Yazdani A, Samiei A, Boerwinkle E (2016) Identification, analysis, and interpretation of a human serum metabolomics causal network in an observational study. J Biomed Informatics 63: 337-343.
Yazdani A, Yazdani A, Boerwinkle E (2016) A causal network analysis of the fatty acid metabolome in African-Americans reveals a critical role for palmitoleate and margarate. OMICS: A J Integrative Biol 20: 480-484.
Yazdani A, Yazdani A, Saniei A, Boerwinkle E (2016) A causal network analysis in an observational study identifies metabolomics pathways influencing plasma triglyceride levels. Metabolomics 12: 1-7.
Yazdani A, Yazdani A, Boerwinkle E (2016) Conceptual aspects of causal networks in an applied context. J Data Mining Geno Proteo 7: 2153-0602.
Yazdani A, Yazdani A, Samiei A, Boerwinkle E (2016) Generating a robust statistical causal structure over 13 cardiovascular disease risk factors using genomics data. J Biomed Informatics 60: 114-119.
Ch�¡vez-Galarza J, Garnery L, Henriques D, Neves CJ, Loucif-Ayad W, et al. (2016) Mitochondrial DNA variation of Apis mellifera iberiensis: further insights from a large-scale study using sequence data of the tRNAleu-cox2 intergenic region. Apidologie 1-2.
The role of MicroRNAs in defense against viral phytopathogens
Computational Identification of MicroRNAs and Their Transcript Target(s) in Field Mustard (Brassica rapa L.).
Validation and quality assessment of macromolecular structures using complex network analysis.
Heinke F, Bittrich S, Kaiser F, Labudde D (2016) SequenceCEROSENE: a computational method and web server to visualize spatial residue neighborhoods at the sequence level. BioData mining 9: 6.
Usman T, Hadlich F, Demasius W, Weikard R, K�¼hn C (2017) Unmapped reads from cattle RNAseq data: A source for missing and misassembled sequences in the reference assemblies and for detection of pathogens in the host. Genomics 109: 36-42.
Fu YB, Yang MH (2017) Genotyping-by-Sequencing and Its Application to Oat Genomic Research. Oat: Methods and Protocols 169-187.
Genomic Characterization of Lactobacillus delbrueckii TUA4408L and Evaluation of the Antiviral Activities of its Extracellular Polysaccharides in Porcine Intestinal Epithelial Cells.
A Survey on Machine Learning Techniques for Cyber Security in the Last Decade
Performance Comparison and Current Challenges of Using Machine Learning Techniques in Cybersecurity
Riccadonna S, Jurman G, Visintainer R, Filosi M, Furlanello C (2016) DTW-MIC coexpression networks from time-course data. PloS one 11: e0152648.
Poljak M (2016) Next-generation sequencing: a diagnostic one-stop shop for hepatitis C?. J Clin Microbiol. 54: 2427-2430.
Posada-Cespedes S, Seifert D, Beerenwinkel N (2016) Recent advances in inferring viral diversity from high-throughput sequencing data. Virus Research.