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Journal of Proteomics & Bioinformatics

Journal of Proteomics & Bioinformatics
Open Access

ISSN: 0974-276X

+44 1223 790975

Journal of Proteomics & Bioinformatics : Citations & Metrics Report

Articles published in Journal of Proteomics & Bioinformatics have been cited by esteemed scholars and scientists all around the world. Journal of Proteomics & Bioinformatics has got h-index 32, which means every article in Journal of Proteomics & Bioinformatics has got 32 average citations.

Following are the list of articles that have cited the articles published in Journal of Proteomics & Bioinformatics.

  2021 2020 2019 2018 2017 2016

Year wise published articles

64 15 21 31 45 47

Year wise citations received

524 565 544 497 546 567
Journal total citations count 5474
Journal impact factor 10.40
Journal 5 years impact factor 16.58
Journal cite score 18.65
Journal h-index 32
Journal h-index since 2018 22
Important citations (453)

ceciliani f, roccabianca p, giudice c, lecchi c (2016) application of post-genomic techniques in dog cancer research. mol biosyst 12:2665-2679.

maria-neto s, de almeida kc, macedo ml, franco ol (2015) understanding bacterial resistance to antimicrobial peptides: from the surface to deep inside. biochimica et biophysica acta. 1848:3078-3088.

xiao x, wu yt (2015) irspot-gcfpsenc: identifying recombination spots with pseudo nucleotide composition. biomedical engineering and environmental engineering 6:3.

tiwari ak, srivastava r (2018) an efficient approach for prediction of nuclear receptor and their subfamilies based on fuzzy k-nearest neighbor with maximum relevance minimum redundancy. proc natl acad sci india a 88:129-136.

tiwari ak, srivastava r (2015) feature based classification of nuclear receptors and their subfamilies using fuzzy k-nearest neighbor. in2015 international conference on advances in computer engineering and applications. ieee pp. 24-28.

zhang l, zhang c, gao r, yang r (2015) jppred: prediction of types of j-proteins from imbalanced data using an ensemble learning method. biomed res int 2015.

ismail hd, saigo h, kc db (2018) rf-nr: random forest based approach for improved classification of nuclear receptors. ieee/acm transactions on computational biology and bioinformatics (tcbb) 15:1844-1852.

zhang l, zhang c, gao r, yang r (2015) incorporating g-gap dipeptide composition and position specific scoring matrix for identifying antioxidant proteins. in2015 ieee 28th canadian conference on electrical and computer engineering (ccece). ieee pp. 31-36.

nebel jc (2014) computational intelligence in bioinformatics. j proteomics bioinform s 9:2.

tiwari ak, srivastava r (2015) an efficient approach for the prediction of ion channels and their subfamilies. comput biol chem 58:205-221.

zhang l, zhang c, gao r, yang r, song q (2016) sequence based prediction of antioxidant proteins using a classifier selection strategy. plos one 11:e0163274.

zhang l, zhang c, gao r, yang r, song q (2016) using the smote technique and hybrid features to predict the types of ion channel-targeted conotoxins. j theor biol 403:75-84.

zhang l, zhang c, gao r, yang r (2015) an ensemble method to distinguish bacteriophage virion from non-virion proteins based on protein sequence characteristics. int j mol sci 16:21734-21758.

tiwari ak, srivastava r (2014) a survey of computational intelligence techniques in protein function prediction. international journal of proteomics 2014.

ng s (2019) multi-omics analysis of immune-metabolic blood responses of very preterm infants for improving diagnosis of late-onset sepsis (doctoral dissertation, murdoch university).

rusconi b, good m, warner bb (2017) the microbiome and biomarkers for necrotizing enterocolitis: are we any closer to prediction? j pediatr 189:40-47.

samuel bo, folashade o (2018) nanoscale science and nanotechnology education in africa: importance and challenges. afr j chem educ 8:7-27.

ng s, strunk t, jiang p, muk t, sangild pt, currie a, et al. (2018) precision medicine for neonatal sepsis. front mol biosci 5:70.

rusconi b, good m, warner bb (2017) the microbiome and biomarkers for necrotizing enterocolitis: are we any closer to prediction? j pediatr 189:40-47.

riveros c, ujaldon m, moscato p (2016) gpu acceleration of an entropy-based model to quantify epistatic interactions between snps. curr bioinform 11:396-407.

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