+44-77-2385-9429Immunome Research : Citations & Metrics Report
Articles published in Immunome Research have been cited by esteemed scholars and scientists all around the world. Immunome Research has got h-index 15, which means every article in Immunome Research has got 15 average citations.
Following are the list of articles that have cited the articles published in Immunome Research.
| 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | |
|---|---|---|---|---|---|---|---|---|
Total published articles |
30 | 37 | 20 | 40 | 13 | 7 | 20 | 17 |
Conference proceedings |
0 | 0 | 0 | 0 | 0 | 0 | 99 | 44 |
Citations received as per Google Scholar, other indexing platforms and portals |
74 | 82 | 94 | 111 | 117 | 98 | 76 | 71 |
| Journal total citations count | 952 |
| Journal impact factor | 9.00 |
| Journal 5 years impact factor | 10.13 |
| Journal cite score | 13.75 |
| Journal h-index | 15 |
| Journal h-index since 2019 | 13 |
Important citations (1540)
cohn m (2007) conceptualizing the self-nonself discrimination by the vertebrate immune system. inin silico immunology. springer us, pp: 375-398. |
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dimitrov i, garnev p, flower dr, doytchinova i (2010) peptide binding to the hla-drb1 supertype: a proteochemometrics analysis. european journal of medicinal chemistry 45: 236-243. |
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karpenko o, huang l, dai y (2008) a probabilistic meta-predictor for the mhc class ii binding peptides. immunogenetics 60: 25-36. |
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tsurui h, takahashi t (2007) prediction of t-cell epitope. journal of pharmacological sciences 105: 299-316. |
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diezâ€rivero cm, chenlo b, zuluaga p, reche pa (2010) quantitative modeling of peptide binding to tap using support vector machine. proteins: structure, function, and bioinformatics 78: 63-72. |
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bahara nh, tye gj, choong ys, ong eb, ismail a, lim ts (2013) phage display antibodies for diagnostic applications. biologicals 41: 209-216. |
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o'brien c, flower dr, feighery c (2008) peptide length significantly influences in vitro affinity for mhc class ii molecules. immunome research 4: 6. |
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salimi n, fleri w, peters b, sette a (2010) design and utilization of epitope-based databases and predictive tools. immunogenetics. 62: 185-196. |
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magnan cn, zeller m, kayala ma, vigil a, randall a, et al. (2010) high-throughput prediction of protein antigenicity using protein microarray data. bioinformatics 26: 2936-2943. |
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doytchinova ia, flower dr (2006) class i t-cell epitope prediction: improvements using a combination of proteasome cleavage, tap affinity, and mhc binding. molecular immunology 43: 2037-2044. |
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zhou p, tian f, wu y, li z, shang z (2008) quantitative sequence-activity model (qsam): applying qsar strategy to model and predict bioactivity and function of peptides, proteins and nucleic acids. current computer-aided drug design 4: 311-321. |
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vita r, vaughan k, zarebski l, salimi n, fleri w, et al. (2006) curation of complex, context-dependent immunological data. bmc bioinformatics 7: 341. |
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ansari hr, flower dr, raghava gp (2010) antigendb: an immunoinformatics database of pathogen antigens. nucleic acids research 38: d847-853. |
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zhang gl, ansari hr, bradley p, cawley gc, hertz t, et al. (2014) machine learning competition in immunology–prediction of hla class i binding peptides. |
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chen sw, van regenmortel mh, pellequer jl (2009) structure-activity relationships in peptide-antibody complexes: implications for epitope prediction and development of synthetic peptide vaccines. current medicinal chemistry 16: 953-964. |
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roomp k, antes i, lengauer t (2010) predicting mhc class i epitopes in large datasets. bmc bioinformatics 11: 90. |
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landais e, romagnoli pa, corper al, shires j, altman jd, et al. (2009) new design of mhc class ii tetramers to accommodate fundamental principles of antigen presentation. the journal of immunology 183: 7949-7957. |
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pappalardo f, halling-brown md, rapin n, zhang p, alemani d, et al. (2009) immunogrid, an integrative environment for large-scale simulation of the immune system for vaccine discovery, design and optimization. briefings in bioinformatics 10: 330-340. |
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ponomarenko jv, van regenmortel mh (2009) b cell epitope prediction. structural bioinformatics pp: 849-879. |
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wang hw, lin yc, pai tw, chang ht (2011) prediction of b-cell linear epitopes with a combination of support vector machine classification and amino acid propensity identification. biomed research international. |
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