The DOI matches its Crossref record; 77 of the 80 references it cites were found in a registry or an index.
Current progress of immunoinformatics approach harnessed for cellular- and antibody-dependent vaccine design
Open accessAbstract
Immunoinformatics plays a pivotal role in vaccine design, immunodiagnostic development, and antibody production. In the past, antibody design and vaccine development depended exclusively on immunological experiments which are relatively expensive and time-consuming. However, recent advances in the field of immunological bioinformatics have provided feasible tools which can be used to lessen the time and cost required for vaccine and antibody development. This approach allows the selection of immunogenic regions from the pathogen genomes. The ideal regions could be developed as potential vaccine candidates to trigger protective immune responses in the hosts. At present, epitope-based vaccines are attractive concepts which have been successfully trailed to develop vaccines which target rapidly mutating pathogens. In this article, we provide an overview of the current progress of immunoinformatics and their applications in the vaccine design, immune system modeling and therapeutics.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“From a therapeutic perspective, knowledge of the epitope can be used for rational design in targeting an immunogenic region for vaccine development [162].”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [162]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
1 retracted
Zeinalzadeh, N., Salmanian, A. H., Ahangari, G., Sadeghi, M., Amani, J., Bathaie, S. Z., & Jafari, M. (2013) · Biotechnology and Applied Biochemistry · doi:10.1002/bab.1196 · Cited by 13
RetractedSYFPEITHI: database for MHC ligands and peptide motifs
Rammensee, H., Bachmann, J., Emmerich, N., Bachor, O. A., & Stevanović, S. (1999) · Immunogenetics · doi:10.1007/s002510050595 · Cited by 2,316
Prediction of continuous B‐cell epitopes in an antigen using recurrent neural network
Saha, S., & Raghava, G. P. S. (2006) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.21078 · Cited by 1,769
BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes
Jespersen, M. C., Peters, B., Nielsen, M., & Marcatili, P. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx346 · Cited by 1,739
ElliPro: a new structure-based tool for the prediction of antibody epitopes
Ponomarenko, J. V., Bui, H., Li, W., Fusseder, N., Bourne, P. E., Sette, A., & Peters, B. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-514 · Cited by 1,738
Parker, K. C., Bednarek, M. A., & Coligan, J. E. (1994) · The Journal of Immunology · doi:10.4049/jimmunol.152.1.163 · Cited by 1,368
The immune epitope database (IEDB) 3.0
Vita, R., Overton, J. A., Greenbaum, J. A., Ponomarenko, J., Clark, J., Cantrell, J. R., Wheeler, D., Gabbard, J., Hix, D., Sette, A., et al. (2014) · Nucleic Acids Res. · doi:10.1093/nar/gku938 · Cited by 1,086
Reliable prediction of T‐cell epitopes using neural networks with novel sequence representations
Nielsen, M., Lundegaard, C., Worning, P., Lauemøller, S. L., Lamberth, K., Buus, S., Brunak, S., & Lund, O. (2003) · Protein Science · doi:10.1110/ps.0239403 · Cited by 1,075
Edward Jenner and the History of Smallpox and Vaccination
Riedel, S. F. (2005) · Baylor University Medical Center Proceedings · doi:10.1080/08998280.2005.11928028 · Cited by 965
ProPred: prediction of HLA-DR binding sites
Singh, H., & Raghava, G. P. S. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.12.1236 · Cited by 844
Research works printed but not linked: 5
- 10.1007/978-1-4939-1115-8 · DOI
- 10.1002/jmr.v21:4 · DOI
- 10.1002/bab.2014.61.issue-5 · DOI
- Saha SaR GPS. editor BcePred: Prediction of continuous B-cell epitopes in antigenic sequences using physico-chemical properties2004. Catania Sicily, Italy: Artificial Immune Systems: Third international conference, ICARIS; 2004 Sep 13–16.
- 10.1002/prot.v69:2 · DOI
Cited by
Sorted by citations
Computational approaches to therapeutic antibody design: established methods and emerging trends
Norman, R. A., Ambrosetti, F., Bonvin, A. M. J. J., Colwell, L. J., Kelm, S., Kumar, S., & Krawczyk, K. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbz095 · Cited by 219
“From a therapeutic perspective, knowledge of the epitope can be used for rational design in targeting an immunogenic region for vaccine development [162].”
BackgroundAyyagari, V. S., Venkateswarulu, T. C., Peele, K. A., & Srirama, K. (2020) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2020.1850357 · Cited by 146
“…with the conventional approaches and there are examples of the successful development of vaccine candidates by adopting in silico approaches (Ada et al., 2018; Bhatnager et al., 2020; He et al., 2010; Kim et al., 2019; Oli et al., 2020; Patronov & Doytchinova, 2013; Tordello et al., 2017…”
BackgroundNaz, A., Shahid, F., Butt, T. T., Awan, F. M., Ali, A., & Malik, A. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.01663 · Cited by 130
Safavi, A., Kefayat, A., Mahdevar, E., Abiri, A., & Ghahremani, F. H. (2020) · Vaccine · doi:10.1016/j.vaccine.2020.10.016 · Cited by 124
“However, recent advances in the field of immunological bioinformatics have provided feasible tools which can significantly decrease the time and cost required for vaccine development [3,4].”
The advances in brucellosis vaccines
Hou, H., Liu, X., & Peng, Q. (2019) · Vaccine · doi:10.1016/j.vaccine.2019.05.084 · Cited by 117
Qamar, M. T. U., Shokat, Z., Muneer, I., Ashfaq, U. A., Javed, H., Anwar, F., Bari, A., Zahid, B., & Saari, N. (2020) · Vaccines · doi:10.3390/vaccines8020288 · Cited by 100
Ikram, A., Zaheer, T., Awan, F. M., Obaid, A., Naz, A., Hanif, R., Paracha, R. Z., Ali, A., Naveed, A. K., & Janjua, H. A. (2018) · Scientific Reports · doi:10.1038/s41598-018-34254-5 · Cited by 101
Predicting epitopes for vaccine development using bioinformatics tools
Yurina, V., & Adianingsih, O. R. (2022) · Therapeutic Advances in Vaccines and Immunotherapy · doi:10.1177/25151355221100218 · Cited by 98
“41 The three main public repositories containing information on available databases and tools related to immunoinformatics are (1) Nucleic Acids Research Database Annual Issue, (2) Canadian Bioinformatics Links Directory, and (3) Immune Epitope Database and Analysis Resources (IEDB).”
Nain, Z., Karim, M. M., Sen, M. K., & Adhikari, U. K. (2020) · Molecular Immunology · doi:10.1016/j.molimm.2020.02.009 · Cited by 85
Foroutan, M., Ghaffarifar, F., Sharifi, Z., & Dalimi, A. (2020) · Comparative Immunology Microbiology and Infectious Diseases · doi:10.1016/j.cimid.2020.101413 · Cited by 86
Khan, T., Islam, M. J., Parihar, A., Islam, R., Jerin, T. J., Dhote, R., Ali, M., Laura, F. K., & Halim, M. A. (2021) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2021.100578 · Cited by 84
“The production and development of vaccines is relatively cost effective, yet a laborious and time-consuming process [31,32].”
Bioinformatics analysis of ROP8 protein to improve vaccine design against Toxoplasma gondii
Foroutan, M., Ghaffarifar, F., Sharifi, Z., Dalimi, A., & Pirestani, M. (2018) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2018.04.033 · Cited by 61
Chakraborty, C., Sharma, A. R., Bhattacharya, M., Sharma, G., & Lee, S. (2021) · Archives of Medical Research · doi:10.1016/j.arcmed.2021.01.004 · Cited by 64
Khan, T., Islam, R., Jerin, T. J., Mahmud, A., Khatun, S., Kobir, A., Islam, M. N., Akter, A., & Mondal, S. I. (2021) · PLoS ONE · doi:10.1371/journal.pone.0253393 · Cited by 57
“Recent advances in computational biology, immunoinformatics, and reverse vaccinology can facilitate in designing safe and efficient vaccines in a time and cost-effective manner [29,98].”
BackgroundQamar, M. T. U., Ismail, S., Ahmad, S., Mirza, M. U., Abbasi, S. W., Ashfaq, U. A., & Chen, L. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.669812 · Cited by 54
“The main objective of immunoinformatics is to underline immunodominant, safe, and antigenic epitopes, which can evoke strong and safe immunological responses against the pathogen and ful fi l all vaccine candidacy benchmarks (27).”
BackgroundSoleymani, S., Tavassoli, A., & Housaindokht, M. R. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.105057 · Cited by 59
Proteome Wide Screening of Potential Vaccine Targets Against Brucella Melitensis
Malik, M., Ullah, A., Haq, M. U., Sanami, S., Ahmad, S., Khan, S., Al-Harbi, A. I., Abideen, S. A., Irfan, M., Afsheen, Z., et al. (2022) · Vaccines · doi:10.2139/ssrn.4187627 · Cited by 48
Pritam, M., Singh, G., Swaroop, S., Singh, A. K., Pandey, B. K., & Singh, S. P. (2020) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2020.04.191 · Cited by 44
“…that assisted in the preclinical and clinical studies of several vaccine project including Hepatitis B Virus, Dengue, Schistosoma haematobium , Treponema pallidum , S. aureus , Trypanosoma cruzi , Helicobacter pylori , Middle East Respiratory Syndrome Coronavirus, Zika virus [26,45,119,120].”
Umar, A., Haque, A., Alghamdi, Y. S., Mashraqi, M., Rehman, A., Shahid, F., Khurshid, M., & Ashfaq, U. (2021) · Vaccines · doi:10.3390/vaccines9111373 · Cited by 35
“Even though immunological experiments are the most powerful immune modalities, developing a vaccine based on them is pretty time-consuming and costly [63,64].”
BackgroundBhattacharya, M., Sharma, A. R., Ghosh, P., Patra, P., Patra, B. C., Lee, S., & Chakraborty, C. (2022) · Molecular Biotechnology · doi:10.1007/s12033-021-00432-6 · Cited by 36
Skariyachan, S., Taskeen, N., Ganta, M., & Krishna, B. V. (2019) · Critical Reviews in Microbiology · doi:10.1080/1040841x.2019.1600472 · Cited by 36
“…Antibody epitope prediction Various epitope prediction tools and servers Dubey et al. (2018) Identification of biofilm associated protein (BAP) as potential drug targets Prediction of antigenic determinants Major computational biology tools Kazi et al. (2018) Rahbar et al. (2010) baumannii.”
BackgroundImmunoinformatics and Epitope Prediction
Ramana, J., & Mehla, K. (2020) · Methods in molecular biology · doi:10.1007/978-1-0716-0389-5_6 · Cited by 37
Albutti, A. (2021) · Scientific Reports · doi:10.1038/s41598-021-01283-6 · Cited by 36
Leow, C. Y., Kazi, A., Ismail, C. M. K. H., Chuah, C., Lim, B. H., Leow, C. Y., & Singh, K. K. B. (2020) · Clinical and Experimental Vaccine Research · doi:10.7774/cevr.2020.9.1.15 · Cited by 33
“In this study, five OMPs selected by immunoinformatics method were found to possess numbers of antigenic epitopes which could potentially induce both humoral (B-) and cellular (Tcell) mediated immune responses [42].”
Saba, A. A., Adiba, M., Saha, P., Hosen, M. I., Chakraborty, S., & Nabi, A. N. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.104703 · Cited by 33
TTAgP 1.0: A computational tool for the specific prediction of tumor T cell antigens
Lissabet, J. F. B., Belén, L. H., & Farías, J. G. (2019) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2019.107103 · Cited by 31
Aldakheel, F., Abrar, A., Munir, S., Aslam, S., Allemailem, K. S., Khurshid, M., & Ashfaq, U. (2021) · Vaccines · doi:10.3390/vaccines9101079 · Cited by 33
Ghaffari, A. D., Dalimi, A., Ghaffarifar, F., & Pirestani, M. (2020) · Microbial Pathogenesis · doi:10.1016/j.micpath.2020.104079 · Cited by 31
Chao, P., Zhang, X.-Q., Zhang, L., Yang, A., Wang, Y., & Chen, X. (2024) · Scientific Reports · doi:10.1038/s41598-024-55372-3 · Cited by 32
Mohammed, A. A., Shantier, S. W., Mustafa, M. I., Osman, H. K., Elmansi, H. E., Osman, I.-A. A., Mohammed, R. A., Abdelrhman, F. A., Elnnewery, M. E., Yousif, E. M., et al. (2020) · Journal of Immunology Research · doi:10.1155/2020/2567957 · Cited by 29
Bhattacharya, M., Sharma, A. R., Ghosh, P., Lee, S., & Chakraborty, C. (2021) · Aging and Disease · doi:10.14336/ad.2021.0518 · Cited by 28
“Our vaccine development strategies using immunoinformatics and bioinformatics approaches are fast, precise, cost-effective, and reliable against pathogens [19, 20].”
BackgroundSUNITA, S., Singhvi, N., Singh, Y. P., & Shukla, P. (2020) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2020.104357 · Cited by 23
Majidiani, H., Dalimi, A., Ghaffarifar, F., Pirestani, M., & Ghaffari, A. D. (2020) · Microbial Pathogenesis · doi:10.1016/j.micpath.2020.104386 · Cited by 23
Rostamian, M., Farasat, A., Lorestani, R. C., Zargaran, F. N., Ghadiri, K., & Akya, A. (2020) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2020.1810126 · Cited by 23
“Since evaluation of individual vaccines under in vivo conditions is an enduring task, bioinformatics approaches can offer an alternative, attractive, cost-effective, and much easier way to evaluate antigens and their more potent parts (epitopes) as vaccine candidates (Kazi et al., 2018).”
BackgroundB-Cell Epitope Predictions Using Computational Methods
Zheng, D., Liang, S., & Zhang, C. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2609-2_12 · Cited by 22
In-Silico Proteomic Exploratory Quest: Crafting T-Cell Epitope Vaccine Against Whipple’s Disease
Joshi, A., & Kaushik, V. (2020) · International Journal of Peptide Research and Therapeutics · doi:10.1007/s10989-020-10077-9 · Cited by 21
“It allow the choice in hands of human interface for selecting antigens from pathogenic set of DNA and most antigenic areas could be used to synthesize potential immunization to initiate defensive responses against harmful pathogenic species (Ada et al. 2018).”
BackgroundComputational design of a novel multi-epitope vaccine candidate against group A rotavirus
Pajand, O., Larimi, A. G., Ahmad, S., Mahooti, M., Mohammadi, G., & Sanami, S. (2026) · Virology Journal · doi:10.1186/s12985-026-03099-0 · Cited by 20
“Recent advances in reverse vaccinology, immunoinfor-matics, and computational biology have the potential to significantly cut the time and cost required to manufacture safe and effective vaccines [20, 21].”
An In Silico Deep Learning Approach to Multi-Epitope Vaccine Design: A Hepatitis E Virus Case Study
Ikram, A., Alzahrani, B., Zaheer, T., Sattar, S., Rasheed, S., Aurangzeb, M., & Ishaq, Y. (2023) · Vaccines · doi:10.3390/vaccines11030710 · Cited by 18
Wang, H., Hao, X., He, Y., & Fan, L. (2024) · PLoS ONE · doi:10.1371/journal.pone.0296737 · Cited by 18
Systems Biology Approaches for Therapeutics Development Against COVID-19
Jaiswal, S., Kumar, M., Mandeep, SUNITA, S., Singh, Y. P., & Shukla, P. (2020) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2020.560240 · Cited by 17
Design of a Multi-epitope Vaccine Against Acinetobacter baumannii Using Immunoinformatics Approach
Touhidinia, M., Sefid, F., & Bidakhavidi, M. (2021) · International Journal of Peptide Research and Therapeutics · doi:10.1007/s10989-021-10262-4 · Cited by 18
“Immunoinformatics plays a key role in vaccine design and antibody production (Kazi et al. 2018).”
BackgroundNosrati, M. C., Ghasemi, E., Shams, M., Shamsinia, S., Yousefi, A., Nourmohammadi, H., Javanmardi, E., Kordi, B., Majidiani, H., Ghaffari, A. D., et al. (2020) · Microbial Pathogenesis · doi:10.1016/j.micpath.2020.104488 · Cited by 17
Alnajran, H., Awadalla, M., Aldakheel, F. M., Alam, I. S., Momin, A. A., Alturaiki, W., & Alosaimi, B. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1546254 · Cited by 15
“Recent advancements in computational biology, immunoinformatics, and reverse vaccinology hold promise for accelerating the development of safe and effective vaccines in a more time-and cost-ef fi cient manner (39, 40).”
Computational-Driven Epitope Verification and Affinity Maturation of TLR4-Targeting Antibodies
Ahmad, S. B., Batool, M., Kim, M.-S., & Choi, S. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22115989 · Cited by 13
Aminnezhad, S., Ali, A. A., Ghazanfari, T., Bandehpour, M., & Zarrabi, M. (2020) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2020.104462 · Cited by 15
Deep learning in next-generation vaccine development for infectious diseases
Bhattacharya, M., Lo, Y.-H., Chatterjee, S., Das, A., Wen, Z., & Chakraborty, C. (2025) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2025.102586 · Cited by 19
“114 The construction of a multiepitope vaccine candidate using several antigenic structures has been expedited using this technique.”
Ghaffari, A. D., Dalimi, A., Ghaffarifar, F., Pirestani, M., & Majidiani, H. (2021) · Clinical and Experimental Vaccine Research · doi:10.7774/cevr.2021.10.1.59 · Cited by 14
Hashempour, T., Khodadad, N., Bemani, P., Ghasemi, Y., Akbarinia, S., Bordbari, R., Tabatabaei, A. H., & Falahi, S. (2024) · PLoS ONE · doi:10.1371/journal.pone.0306559 · Cited by 13
Ghaffari, A. D., Dalimi, A., Ghaffarifar, F., & Pirestani, M. (2020) · Clinical and Experimental Vaccine Research · doi:10.7774/cevr.2020.9.2.81 · Cited by 13
“53% and this server permits users to predict epitopes of B-cell using any of the physico-chemical properties (accessibility, hydrophilicity, polarity, flexibility/mobility, exposed surface, and turns) [39].”
BackgroundDesign of a multi-epitope Zika virus vaccine candidate – an in-silico study
Ezzemani, W., Windisch, M. P., Altawalah, H., Guessous, F., Saı̈le, R., Benjelloun, S., Kettani, A., & Ezzikouri, S. (2022) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2022.2055648 · Cited by 13
“For the protein structure refinement, the predicted model was refined by GalaxyRefine server (Heo et al., 2013; Ko et al., 2012).”
MethodCulma, M. F. (2020) · Microbial Pathogenesis · doi:10.1016/j.micpath.2020.104545 · Cited by 13
Khan, T., Mahmud, A., Islam, M. M., Sumaia, M. S. N., Rahim, Z., Islam, K., & Iqbal, A. (2023) · Genomics & Informatics · doi:10.5808/gi.23021 · Cited by 12
“Traditional vaccine development is a time-consuming, laborious, and expensive process [35,141].”
BackgroundLeow, C. Y., Willis, C., Chuah, C., Leow, C. H., & Jones, M. K. (2019) · Parasite Immunology · doi:10.1111/pim.12693 · Cited by 12
Kazi, A., Ismail, C. M. K. H., Anthony, A. A., Chuah, C., Leow, C. Y., Lim, B. H., Singh, K. K. B., & Leow, C. Y. (2020) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2020.104176 · Cited by 12
Lim, C. P., Kok, B. H., Lim, H. T., Chuah, C., Abdul‐Rahman, B., Majeed, A. B. A., Wykes, M., Leow, C. Y., & Leow, C. Y. (2022) · Pathogens and Global Health · doi:10.1080/20477724.2022.2072456 · Cited by 12
“regulatory analysis of sequence-based or molecular data, modelling of immunologic data and immunologic databases as well as simulation of wet-laboratory experiments [37,38].”
BackgroundVeisi, R., Nazarian, S., Fathi, J., & Hadi, N. (2024) · Microbial Pathogenesis · doi:10.1016/j.micpath.2024.106539 · Cited by 11
Recombinant Vaccine Design Against Clostridium spp. Toxins Using Immunoinformatics Tools
Rodrigues, R. R., Ferreira, M. R. A., Kremer, F. S., Donassolo, R. A., Moreira, C., Alves, M. L. F., & Conceição, F. R. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1892-9_25 · Cited by 10
Multi epitope vaccine candidate design against Streptococcus pneumonia
Devarakonda, Y., Reddy, M. V. N. J., Neethu, R. S., Chandran, A., & Syal, K. (2023) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2023.2167123 · Cited by 10
“The current progress and developments in the field of immunoinformatics have made it possible to develop vaccine in cost-effective and timely manner (Kazi et al., 2018).”
BackgroundHosseininejad, Z., Daryani, A., Fasihi‐Ramandi, M., Asgarian‐Omran, H., Valadan, R., Nayeri, T., Dodangeh, S., & Sarvi, S. (2023) · Iranian Journal of Parasitology · doi:10.18502/ijpa.v18i3.13753 · Cited by 9
“In addition, designed vaccines are more efficient and safer than traditional vaccines (32).”
BackgroundHakimian, M., Doosti, A., & Sharifzadeh, A. (2024) · BMC Immunology · doi:10.1186/s12865-024-00617-z · Cited by 8
“The primary benefit of this technology is its ability to detect many candidate vaccinations without spreading bacterial illnesses across a wet laboratory [22].”
BackgroundWei, J., Cheng, X., Zhang, Y., Gao, C., Wang, Y., Peng, Q., Luo, P., Yang, L., Zou, Q., Zeng, H., et al. (2021) · Molecular Immunology · doi:10.1016/j.molimm.2021.03.028 · Cited by 8
Ezzemani, W., Kettani, A., Sappati, S., Kondaka, K., Ossmani, H. E., Tsukiyama–Kohara, K., Altawalah, H., Saı̈le, R., Kohara, M., Benjelloun, S., et al. (2022) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2022.2075468 · Cited by 8
“Then, the immune simulation studies were conducted to understand the ability of our vaccine construct to elicit a cellular or hormonal immune response (Kazi et al., 2018).”
BackgroundSharma, S. K., Srivastava, S., Kumar, A., & Srivastava, V. P. (2021) · International Journal of Peptide Research and Therapeutics · doi:10.1007/s10989-021-10219-7 · Cited by 8
“The ever-expanding human population, widening interaction between humans and animals, dynamic environmental conditions, and poor sanitation are the main reasons for the outbreaks of zoonotic diseases (Kazi et al. 2018).”
BackgroundKhan, A., Zahid, M., Farrukh, F., Abdelsalam, S. S., Mohammad, A., Al‐Zoubi, R. M., Shkoor, M., Hssain, A. A., Wei, D., & Agouni, A. (2024) · International Immunopharmacology · doi:10.1016/j.intimp.2024.112833 · Cited by 7
Heidarinia, H., Tajbakhsh, E., Bahrami, Y., & Rostamian, M. (2025) · AMB Express · doi:10.1186/s13568-025-01913-6 · Cited by 10
“To address this challenge, bioinformatics methods using epitope prediction algorithms have been developed, which have significantly reduced the cost and time of epitope identification (Kazi et al. 2018).”
Heidarinia, H., Tajbakhsh, E., Rostamian, M., & Momtaz, H. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e18614 · Cited by 7
EpiCurator: an immunoinformatic workflow to predict and prioritize SARS-CoV-2 epitopes
Ferreira, C. D. S., Martins, Y., Souza, R. C., & de Vasconcelos, A. T. R. (2021) · PeerJ · doi:10.7717/peerj.12548 · Cited by 7
“This approach regards the wide availability of the SARS-CoV-2 NGS (Next-Generation Sequencing) information associated with human leukocyte antigen (HLA) profile (Kazi et al., 2018; Oli et al., 2020; Sharma et al., 2020) to identify T cell epitopes.”
MethodGupta, N., Khan, F., & Kumar, A. (2018) · International Journal of Peptide Research and Therapeutics · doi:10.1007/s10989-018-9764-z · Cited by 7
“It allows the selection of antigenic regions from the pathogenic genomes and the most antigenic regions could be developed as potential vaccine candidates to trigger protective immune responses (Ada et al. 2018).”
BackgroundZaher, M. R., El-Husseiny, M. H., Hagag, N. M., Elamir, A. M., Zowalaty, M. E. E., & Tammam, R. H. (2025) · BMC Veterinary Research · doi:10.1186/s12917-025-04509-1 · Cited by 7
“Immunoinformatics and computational biology have raised the bar in the vaccine production industry through enabling a safer and more innovative way to design viral vaccines [60, 61].”
Ghosh, P., Bhattacharya, M., Patra, P., Sharma, G., Patra, B. C., Lee, S., Sharma, A. R., & Chakraborty, C. (2021) · International Journal of Peptide Research and Therapeutics · doi:10.1007/s10989-021-10322-9 · Cited by 6
Pritam, M., Singh, G., Kumar, R., & Singh, S. P. (2022) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2022.2028676 · Cited by 6
“…Dengue, Fascioliasis, etc. because of convenience, low cost, reduced labor and/or risk of failure of the vaccine in the wet laboratory (Ali et al., 2017; Behbahani et al., 2021; Kaba et al., 2018; Kazi et al., 2018; Rahmani et al., 2019; Singh et al., 2020; Yazdani et al., 2020; Zeb et al., 2021).”
BackgroundMotamedpour, L., Dalimi, A., Pirestani, M., & Ghaffarifar, F. (2020) · PubMed Central · doi:10.22038/ijbms.2020.45394.10561 · Cited by 6
Silva, M. T. D. O., de Pinho, R. B., Bezerra, F. S. B., Scholl, N. R., Moron, L. D., Alves, M. S. D., Woloski, R., Kremer, F. S., & Borsuk, S. (2021) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-021-11619-x · Cited by 6
“1 3 to cultivate the microorganism of interest (Kazi et al. 2018).”
BackgroundLeow, C. Y., Chuah, C., Majeed, A. B. A., Norazmi, M. N., & Leow, C. Y. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1900-1_2 · Cited by 6
Nirob, M. N. H., Sultana, I., Arian, T. A., Islam, M. S., Moniruzzzaman, M., Nosi, S. J., Halder, S. K., Shil, A., & Himel, M. K. (2025) · PLoS ONE · doi:10.1371/journal.pone.0334885 · Cited by 5
“Immunoinformatic research has made significant strides in recent memory, resulting in useful programs and platforms that are helping speed up and lower the expense of developing traditional vaccines [106].”
In Silico Analysis of the ROP29 Protein as a Vaccine Candidate Against Toxoplasma gondii
KarimiPourSaryazdi, A., Ghaffarifar, F., Dalimi, A., Foroutan, M., Horton, J. D., & Sadraei, J. (2024) · Journal of Parasitology Research · doi:10.1155/2024/1918202 · Cited by 5
Foroutan, M., Ghaffari, A. D., Ghaffarifar, F., KarimiPourSaryazdi, A., Birgani, A. A., Majidiani, H., Cortes, H. C. E., & Elsheikha, H. M. (2025) · Journal of Parasitology Research · doi:10.1155/japr/3514414 · Cited by 4
Shabani, N. R. M., Ismail, C. M. K. H., Anthony, A. A., Leow, C. Y., Chuah, C., Majeed, A. B. A., Norazmi, M. N., He, Y., Singh, K. K. B., & Leow, C. Y. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.105900 · Cited by 4
Foroutan, M., & Shadravan, M. M. (2024) · Clinical and Experimental Vaccine Research · doi:10.7774/cevr.2024.13.4.359 · Cited by 4
Zafar, S., Bai, Y.-H., Muhammad, S. A., Guo, J.-L., Khurram, H., Zafar, S., Muqaddas, I., Shaikh, R. S., & Bai, B. (2025) · PLoS ONE · doi:10.1371/journal.pone.0309049 · Cited by 4
Foroutan, M., KarimiPourSaryazdi, A., Ghaffari, A. D., Majidiani, H., Birgani, A. A., Karimzadeh‐Soureshjani, E., Soltani, S., & Elsheikha, H. M. (2025) · Bioinformatics and Biology Insights · doi:10.1177/11779322251315924 · Cited by 5
“41,77,91 The prediction of epitopes primarily relies on several protein structural features.”
Integration: Gospel for immune bioinformatician on epitope-based therapy
Sun, B., Zhang, J., Li, Z., Xie, M., Luo, C., Wang, Y., Chen, L., Wang, Y., Jiang, D., & Yang, K. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1075419 · Cited by 4
“This is probably because of the inherent defects in computer algorithms based on epitope databases for fi tting functions (8, 11).”
Rubab, A., Sarfraz, A., Khan, M. U., Fawy, K. F., & Shah, M. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.111344 · Cited by 3
Ammari, A. A., Alhimaidi, A. R., Amran, R. A., Ghadi, M. G. A., & Rady, A. M. (2023) · Indian Journal of Animal Research · doi:10.18805/ijar.bf-1614 · Cited by 3
Ishaq, Z., Zaheer, T., Waseem, M., Awan, H. S., Ullah, N., Alasmari, A. F., Alasmari, F. F., & Ali, A. (2023) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2023.2266018 · Cited by 3
“While we acknowledge the potential of immunoinfor-matics-based vaccine designs, it’s crucial to understand and address the inherent limitations in this approach (Kazi et al., 2018).”
A Novel Chimeric Antigen as a Vaccine Candidate against Leishmania major: In silico Analysis
Ahmadpour, N. B., Dalimi, A., Pirestani, M., & Sadraei, J. (2021) · Iranian Journal of Parasitology · doi:10.18502/ijpa.v16i2.6267 · Cited by 3
“Meantime, ABCpred server (6, 11) was used.”
BackgroundLi, X., Wen, H., Xiao, X., Ren, Z., Tan, C., & Fu, C. M. (2023) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2023.2263213 · Cited by 3
“The development of immunoinformatics and bioinformatics approaches has significantly accelerated the process of epitope identification and screening by reducing the time and cost required for vaccine design (Kazi et al., 2018).”
Mohammadi, M. K., & Ghaffari, A. D. (2025) · Parasite Immunology · doi:10.1111/pim.70004 · Cited by 5
“Users can predict B cell epitopes considering various chemical and physical characteristics such as polarity, accessibility, hydro-philicity, exposed surface, turns and mobility/flexibility [38, 39].”
Gupta, N., & Kumar, A. (2019) · International Journal of Peptide Research and Therapeutics · doi:10.1007/s10989-019-09933-0 · Cited by 3
“It permits the choice of antigenic locales from the pathogenic genomes and the most antigenic areas could be created as potential immunization possibility to trigger defensive immune responses (Ada et al. 2018).”
BackgroundRahman, M. N., Ahmed, S., Hasan, M., Shuvo, M. S. A., Islam, M. A., Hasan, R., Roy, S., Hossain, H., & Mia, M. M. (2023) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2023.101209 · Cited by 3
Heidarinia, H., Tajbakhsh, E., Rostamian, M., & Momtaz, H. (2023) · Research Square · doi:10.21203/rs.3.rs-3182215/v1 · Cited by 3
Zubair, M., Wang, J., Yu, Y., Rasheed, M. A., Faisal, M. S., Dawood, A. S., Ashraf, M. A., Shao, G., Feng, Z., & Xiong, Q. (2023) · Veterinary Sciences · doi:10.3390/vetsci10090557 · Cited by 2
Mashraqi, M. M., Alzamami, A., Alturki, N. A., Almasaudi, H. H., Ahmed, I., Alshamrani, S., & Basharat, Z. (2023) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2023.1258834 · Cited by 2
“Immunoinformatics approaches can accelerate the vaccine design process and reduce the cost by predicting epitopes that are likely to be effective (Kazi et al., 2018).”
BackgroundMohammadhasani, F., Ghaffari, A. D., & Asadi, M. (2024) · Discover Applied Sciences · doi:10.1007/s42452-024-06189-2 · Cited by 1
“Bcepred anticipated continuous B-cell epitopes by considering factors like polarity, hydrophilicity, flexibility, accessibility, turns, and antigenic propensity, achieving accuracies ranging from 58.7% [45, 46].”
InfluentialSingh, S. P., Singh, G., & Mishra, B. N. (2025) · Exploration of Immunology · doi:10.37349/ei.2025.1003215 · Cited by 1
Nayeri, T., Asl, A. D., Ghaffarifar, F., & Moridnia, A. (2025) · The Open Microbiology Journal · doi:10.2174/0118742858411659251007070159 · Cited by 1
Lim, C. P., Bingöl, E. N., de Oliveira, J. J., Chuah, C., Khan, M. A., Douradinha, B. G., Leow, C. Y., & Leow, C. Y. (2026) · Naunyn-Schmiedeberg s Archives of Pharmacology · doi:10.1007/s00210-026-05714-x · Cited by 1
“Advances in immunoinformatics have allowed the development and improvement of in silico tools, which aids in reverse vaccinology for the design of vaccine candidates against diverse pathogens (Lim et al. 2022; Kazi et al. 2018; Lim et al. 2024; Douradinha 2024).”
Developing COVID-19 Vaccines by Innovative Bioinformatics Approaches
Jakhar, R., Sehrawat, N., & Gakhar, S. K. (2021) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-030-68936-0_9 · Cited by 1
Trichinellosis: A Hidden Threat in Meat Consumption
(2023) · International Journal of Agriculture and Biosciences · doi:10.47278/book.zoon/2023.72 · Cited by 1
Metadata
- Authors
- Kazi, A., Chuah, C., Majeed, A. B. A., Leow, C. H., Lim, B. H., & Leow, C. Y.
- Affiliations
- Universiti Sains Malaysia (MY)
- Universiti Teknologi MARA System (MY)
- ,
- Venue
- Pathogens and Global Health
- Publisher
- Informa UK Limited
- Published
- 2018-03-12
- Volume
- 112
- Issue
- 3
- Pages
- 123-131
- ISSN
- 2047-7724 (ISSN-L)
- 2047-7732
- PMC
- PMC6056828
- OpenAlex
- W2789811841
- Cited by
- 122
- References
- 80
- Citations by year
- 2026: 6 · 2025: 19 · 2024: 12 · 2023: 17 · 2022: 9 · 2021: 28 · 2020: 22 · 2019: 6 · 2018: 3
- FWCI
- 5.25
- Type
- journal article
- Language
- en
- Update notices
- correction (2018-04-27)
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Pathogens and Global Health (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Higher Institutions Centre of Excellence Program (311/CIPPM/4401005)
- Fundamental Research Grant Scheme (203/CIPPM/6171199)
- The Malaysian Ministry of Higher Education of the Higher Institutions Centre of Excellence Program (311/CIPPM/4401005)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Immune Systems Applications
- Keywords
- immunoinformatics, vaccine design, antibody design, epitope-based vaccine, immune system modeling, B-cell epitopes
- MeSH terms
- Animals, Epitopes, Humans, Immunity, Cellular, Vaccines, Computational Biology, Drug Discovery, Immunity, Humoral
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review