Articles published in Journal of Computer Science & Systems Biology have been cited by esteemed scholars and scientists all around the world.
Journal of Computer Science & Systems Biology has got h-index 23, which means every article in Journal of Computer Science & Systems Biology has got 23 average citations.
Following are the list of articles that have cited the articles published in Journal of Computer Science & Systems Biology.
2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | |
---|---|---|---|---|---|---|---|
Total published articles |
40 | 43 | 61 | 60 | 41 | 17 | 29 |
Research, Review articles and Editorials |
0 | 0 | 0 | 22 | 25 | 11 | 29 |
Research communications, Review communications, Editorial communications, Case reports and Commentary |
40 | 43 | 61 | 38 | 16 | 6 | 0 |
Conference proceedings |
12 | 0 | 28 | 0 | 0 | 0 | 84 |
Citations received as per Google Scholar, other indexing platforms and portals |
2486 | 2087 | 175 | 232 | 220 | 225 | 205 |
Journal total citations count | 2279 |
Journal impact factor | 1.73 |
Journal 5 years impact factor | 5.97 |
Journal cite score | 5.75 |
Journal h-index | 23 |
Journal h-index since 2019 | 17 |
Priyadarshini V, Pradhan D, Munikumar M, Sandeep S, Umamaheswari A, et al. (2013) Molecular modelling, docking and dynamics studies of biotin carboxyl carrier protein of acetyl-CoA carboxylase to discover potential inhibitors. J Clin Sci Res 2: 72-80. |
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Uddin R, Rafi S (2017) Structural and functional characterization of a unique hypothetical protein (WP_003901628. 1) of Mycobacterium tuberculosis: a computational approach. Medicinal Chemistry Research pp: 1-13. |
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Kyatam SK, Shriram SY, Mashal BS, Saggam AD, Katti AS (2015) In Silico Characterization of Endotoxin: A Future Drug Target for Neisseria meningitidis. International Journal of Advanced Biotechnology and Research 1: 7-11. |
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Ravinarayanan H, Coico R, Sundar K (2015) Identification of putative therapeutic targets in Candida tropicalis: an in silico approach. Trends in Bioinformatics 8: 52. |
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Chavan RAUL, Shinde RAMOD, Girkar KAUSTUB, Mandage R, Chowdhary A (2014) Identification of potent natural inhibitors against H1N1/A/2009 virus using in silico subtractive genomics approach and docking technology. Int J Pharm Res 6: 105-113. |
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NANDODE S, DAMALE M, HARKE S (2012) In silico comparative analysis of metabolic pathways of Heamophilus influenzae and Helicobacter pylori to identify potential drug targets. Int J Pharm Bio Sci 3: 412-420. |
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Vaidya M, Panchal H (2012) In silico investigation and structural characterization of virulent factor and a metallo peptidase present in Helicobacter pylori strain J99. Interdisciplinary sciences, computational life sciences 4: 302. |
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Cooper IAM, Duffield ML (2011) The in silico prediction of bacterial essential genes. Science against microbial pathogens: communicating current research and technological advances. |
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Bhattacharjee B, Simon RM, Gangadharaiah C, Karunakar P (2013) Chemogenomics profiling of drug targets of peptidoglycan biosynthesis pathway in Leptospira interrogans by virtual screening approaches. J Microbiol Biotechnol 23: 779-784. |
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Chordia N, Sharma NK, Kumar A (2015) An interactomic approach for identification of putative drug targets in Listeria monocytogenes. International journal of bioinformatics research and applications 11: 315-325. |
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Prajapati C, Bhagat C (2012) In-Silico Analysis and Homology Modeling Of Target Proteins for Clostridium Botulinum. International Journal of Pharmaceutical Sciences and Research 3: 2050. |
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ANGAMUTHUA K, PIRAMANAYAGAMA S (2012) Insilico identification of putative drug targets in mycoplasma hominis using differential metabolic pathway analysis. Int J Pharm Bio Sci 3: 391-398. |
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Hasan MA, Khan MA, Sharmin T, Mazumder MHH, Chowdhury AS (2016) Identification of putative drug targets in Vancomycin-resistant Staphylococcus aureus (VRSA) using computer aided protein data analysis. Gene 575: 132-143. |
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Muhammad SA, Ahmed S, Ali A, Huang H, Wu X, et al. (2014) Prioritizing drug targets in Clostridium botulinum with a computational systems biology approach. Genomics 104: 24-35. |
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Munikumar M, Priyadarshini V, Pradhan D, Sandeep S, Umamaheswari A, et al. (2012) In silico identification of common putative drug targets among the pathogens of bacterial meningitis. Biochem Anal Biochem 1: 1-7. |
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Priyadarshini V, Pradhan D, Munikumar M, Swargam S, Umamaheswari A, et al. (2013) In silico drug targets for infective endocarditis. Online Journal of Bioinformatics 14: 32-50. |
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Rahman MA, Noore MS, Hasan MA, Ullah MR, Rahman MH, et al. (2014) Identification of potential drug targets by subtractive genome analysis of Bacillus anthracis A0248: An in silico approach. Computational biology and chemistry 52: 66-72. |
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Rana A, Rub A, Akhter Y (2015) Proteomeâ€Âwide B and T cell epitope repertoires in outer membrane proteins of Mycobacterium avium subsp. paratuberculosis have vaccine and diagnostic relevance: a holistic approach. Journal of Molecular Recognition 28: 506-520. |
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Rao Reddy Neelapu N, Pavani T (2013) Identification of novel drug targets in HpB38, HpP12, HpG27, Hpshi470, HpSJM180 strains of Helicobacter pylori: an in silico approach for therapeutic intervention. Current drug targets 14: 601-611. |
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Hosen MI, Tanmoy AM, Salma U, Nazim M, Islam MT, et al. (2014) Application of a subtractive genomics approach for in silico identification and characterization of novel drug targets in Mycobacterium tuberculosis F11. Interdisciplinary sciences, computational life sciences 6: 48. |
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Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report