Integration of Artificial Intelligence and CRISPR/Cas9 System for Vaccine Design

Maserat, Elham

doi:10.1177/11769351221140102

Cited by 7 publications

(5 citation statements)

References 8 publications

(11 reference statements)

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“…Frontiers in Food Science and Technology frontiersin.org AI includes knowledge-based methods (KBMs), machine learning approaches (MLAs), and agent-based models (ABMs) (Maserat, 2022). KBMs can determine the goals of feature selection of allergenic omics data (genomics, transcriptomics, proteomics, metabolomics, and phenomics), biological, and hypersensitive reaction entities.…”

Section: Discussionmentioning

confidence: 99%

Seed storage allergens tackled via next-generation research assistant

Evangelista,

Amoroso,

Nitride

et al. 2024

Front. Food. Sci. Technol.

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The expanding consumption of plant proteins in the diet to overcome the environmental issues associated with animal proteins is increasing the incidence of food-induced allergic reactions. One of the 21st-century research drivers in agriculture sciences is the development and validation of concrete approaches for modulating the expression of allergenic proteins in crops before harvesting. The increasing incidence of plant food allergies is primarily induced by seed storage proteins that clinicians are experiencing recently because of the more predominant use of plant-derived proteins in the food industry. Increased availability of high-throughput technologies has generated an ever-growing number of omics data, allowing us to have better structural knowledge of SSPs and molecular properties that can inform the allergenicity assessment. The recent systems for targeted genome engineering, without double-strand DNA breaks, allow the introduction of precise modifications directly into commercial plant species. Artificial intelligence is significantly transforming scientific research across every stage, assisting scientists, processing large-scale data, making predictions, automating tasks. During this epochal change, marked by the encounter between artificial intelligence and synthetic biology, a next-generation research assistant (NGA) is coming alive. Here, we propose a new conceptual vision to facilitate and speed up the editing of cross-reactivity sites to obtain hypoallergenic cultivars and avoid pleiotropic effects. Finally, we discuss the potential applications of this new way to conceive the research. NGA may be undoubtedly capable of managing the evolution of SPP allergies through the prediction of novel epitopes, as well as the prediction of immunological response mechanisms.

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Section: Discussionmentioning

confidence: 99%

Seed storage allergens tackled via next-generation research assistant

Evangelista,

Amoroso,

Nitride

et al. 2024

Front. Food. Sci. Technol.

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“…Bioinformatics will play a crucial role in identifying molecular subtypes, predicting treatment responses, and developing targeted therapies [11]. Integrating bioinformatics with emerging technologies like CRISPR-Cas9 and AI-driven drug discovery could revolutionize cervical cancer treatment [12].…”

Section: Challenges and Future Directionsmentioning

confidence: 99%

Integrating Bioinformatics in Cervical Cancer Research: A Comprehensive Review

Miao

2024

TMBLS

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In this comprehensive review, we delve into the transformative impact of bioinformatics in cervical cancer research, emphasizing its role in shifting from traditional clinical and pathological approaches to a nuanced molecular and genetic understanding. We explore the evolution of cervical cancer research, highlighting the pivotal transition marked by the identification of human papillomavirus (HPV) and the subsequent advancements in screening and vaccination. Central to this review is the elucidation of bioinformatics' contribution in identifying gene signatures, prognostic markers, and differentially expressed genes, along with the analysis of molecular pathways critical in the progression of cervical cancer. We also examine the methodological intricacies of bioinformatics, from data retrieval and preparation through differential gene expression analysis, to more sophisticated techniques like Gene Set Enrichment and Protein-Protein Interaction Network Analysis. Despite the significant strides made, we acknowledge the challenges in integrating bioinformatics findings into clinical practice and propose future directions towards personalized medicine. This review underscores the pivotal role of bioinformatics in enhancing our understanding of cervical cancer and paves the way for novel diagnostic and therapeutic strategies, ultimately aiming to improve patient care and survival rates.

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“…AIoT in medical care allows technology to work more efficiently with less risk and at a lower cost, 17 thus expanding medical access. Clustered regularly interspaced short palindromic repeats (CRISPR), a technology to improve existing therapies and test drug candidates, is an example of this that uses ML/AI.…”

Section: Quantifying the Benefitsmentioning

confidence: 99%

“…By combining AI and CRISPR technology, researchers can make gene editing more precise, efficient, and reliable. 17 Additionally, the recent application of AIoT in diabetes control highlights the potential of combining IoT technology with predictive models. The AID system is a way of delivering insulin through a pump that communicates with a CGM.…”

Section: Quantifying the Benefitsmentioning

confidence: 99%

The Convergence of the Internet of Things and Artificial Intelligence in Medicine: Assessing the Benefits, Challenges, and Risks

Tommarello,

Deek

2024

Computer

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he integration of tools into health care from emerging technologies, such as the Internet of Things (IoT) and artificial intelligence (AI), has advanced medicine and will continue to do so as their adoption accelerates. There already exist IoT systems that use AI algorithms to help patients manage chronic conditions, assist physicians in diagnosis and treatment, as well as help hospitals track and manage the use of medical equipment and devices.While the use of AI in health care has received considerable attention over the last decade, its initial use can be traced to the expert knowledge systems of the late 1960s and early 1970s. AI has made tremendous advancements in the medical field and is now promising to continue to transform health care. Still, society should be cautious given the implications of unintended consequences. Diagnoses from predictive machine learning (ML) models trained on highly personalized data and the application

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Integration of Artificial Intelligence and CRISPR/Cas9 System for Vaccine Design

Cited by 7 publications

References 8 publications

Seed storage allergens tackled via next-generation research assistant

Seed storage allergens tackled via next-generation research assistant

Integrating Bioinformatics in Cervical Cancer Research: A Comprehensive Review

The Convergence of the Internet of Things and Artificial Intelligence in Medicine: Assessing the Benefits, Challenges, and Risks

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