Genomics DOI

Seyyed Mohammad Amin Mousavi Sagharchi,

Mohsen Sheykhhasan, Atousa Ghorbani

и другие.

Advances in bioinformatics and biomedical engineering book series, Год журнала: 2024, Номер unknown, С. 23 - 68

Опубликована: Сен. 27, 2024

Genomics is an exciting and rapidly evolving field at the intersection of biology, computer science, statistics, which has made remarkable strides in recent years thanks to advancements high-throughput sequencing technologies. This allows us analyze understand genetic code organisms, from humans microorganisms, shedding light on everything diagnosis treatment disorders identification disease-causing genes pathogens, mysteries biodiversity. With its wide range applications, genomics transforming our understanding life itself.

Язык: Английский

Advancing Optical Nanosensors with Artificial Intelligence: A Powerful Tool to Identify Disease-Specific Biomarkers in Multi-omics Profiling DOI
Bakr Ahmed Taha,

Zahraa Mustafa Abdulrahm,

Ali J. Addie

и другие.

Talanta, Год журнала: 2025, Номер 287, С. 127693 - 127693

Опубликована: Фев. 4, 2025

Язык: Английский

Процитировано

4

Advances in bioinformatics and multi-omics integration: transforming viral infectious disease research in veterinary medicine DOI Creative Commons
Alyaa Elrashedy, Walid Mousa,

Mohamed Nayel

и другие.

Virology Journal, Год журнала: 2025, Номер 22(1)

Опубликована: Янв. 31, 2025

The world is changing due to factors like bioterrorism, massive environmental changes, globalization of trade and commerce, growing urbanization, climate, pollution. Numerous diseases have emerged because these factors, especially in companion food-producing animals. pathogens established themselves naïve populations, harming reproduction, productivity, health. Bioinformatics considered a valuable tool infectious disease research, as it provides comprehensive overview the identification pathogens, their genetic makeup, evolutionary relationship. Therefore, there an urgent need for novel bioinformatics approach help decipher model viral epidemiology informatics on domestic animals livestock. With significant advancements NGS, researchers can now identify contigs, which are contiguous sequences DNA that assembled from overlapping fragments, assemble complete genome, perform phylogenetic analysis diagnose, investigate risk animals, handle share large biological datasets across various species. Additionally, multi-omics data integration further deepens our understanding homology, divergence, mutations, relationships, providing perspective molecular mechanisms driving animal infections. This review aims reveal importance utilizing multidisciplinary areas bioinformatics, genomics, proteomics, transcriptomics, metabolomics, metagenomics roles studying veterinary medicine will eventually improve health

Язык: Английский

Процитировано

3

Impact of Metabolites from Foodborne Pathogens on Cancer DOI Creative Commons
Alice Njolke Mafe, Dietrich Büsselberg

Foods, Год журнала: 2024, Номер 13(23), С. 3886 - 3886

Опубликована: Дек. 1, 2024

Foodborne pathogens are microorganisms that cause illness through contamination, presenting significant risks to public health and food safety. This review explores the metabolites produced by these pathogens, including toxins secondary metabolites, their implications for human health, particularly concerning cancer risk. We examine various such as Salmonella sp., Campylobacter Escherichia coli, Listeria monocytogenes, detailing specific of concern carcinogenic mechanisms. study discusses analytical techniques detecting chromatography, spectrometry, immunoassays, along with challenges associated detection. covers effective control strategies, processing techniques, sanitation practices, regulatory measures, emerging technologies in pathogen control. manuscript considers broader highlighting importance robust policies, awareness, education. identifies research gaps innovative approaches, recommending advancements detection methods, preventive policy improvements better manage foodborne metabolites.

Язык: Английский

Процитировано

12

Predictive Modelling in pharmacokinetics: from in-silico simulations to personalized medicine DOI
Ajita Paliwal, Smita Jain, Sachin Kumar

и другие.

Expert Opinion on Drug Metabolism & Toxicology, Год журнала: 2024, Номер 20(4), С. 181 - 195

Опубликована: Март 14, 2024

Pharmacokinetic parameters assessment is a critical aspect of drug discovery and development, yet challenges persist due to limited training data. Despite advancements in machine learning in-silico predictions, scarcity data hampers accurate prediction candidates' pharmacokinetic properties.

Язык: Английский

Процитировано

11

Heavy metal exposure and metabolomics analysis: an emerging frontier in environmental health DOI

Kainat Ilyas,

Hajra Iqbal,

Muhammad Sajid Hamid Akash

и другие.

Environmental Science and Pollution Research, Год журнала: 2024, Номер 31(26), С. 37963 - 37987

Опубликована: Май 23, 2024

Язык: Английский

Процитировано

7

Exploring metabolic anomalies in COVID-19 and post-COVID-19: a machine learning approach with explainable artificial intelligence DOI Creative Commons
Juan José Oropeza-Valdez, Cristian Padrón-Manrique, Aarón Vázquez-Jiménez

и другие.

Frontiers in Molecular Biosciences, Год журнала: 2024, Номер 11

Опубликована: Сен. 9, 2024

The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant challenges worldwide, including diverse clinical outcomes and prolonged post-recovery symptoms known as Long COVID or Post-COVID-19 syndrome. Emerging evidence suggests a crucial role of metabolic reprogramming in the infection's long-term consequences. This study employs novel approach utilizing machine learning (ML) explainable artificial intelligence (XAI) analyze alterations patients. Samples were taken from cohort 142 COVID-19, 48 Post-COVID-19, 38 control patients, comprising 111 identified metabolites. Traditional analysis methods, like PCA PLS-DA, compared with ML techniques, particularly eXtreme Gradient Boosting (XGBoost) enhanced SHAP (SHapley Additive exPlanations) values for explainability. XGBoost, combined SHAP, outperformed traditional demonstrating superior predictive performance providing new insights into basis disease's progression aftermath. revealed metabolomic subgroups within conditions, suggesting heterogeneous responses infection its impacts. Key signatures include taurine, glutamine, alpha-Ketoglutaric acid, LysoPC C16:0. highlights potential integrating XAI fine-grained description metabolomics research, offering more detailed understanding anomalies conditions.

Язык: Английский

Процитировано

3

Microbial Metabolomics for Nutraceutical Developments and Their Applications DOI
Gopinath Ramalingam,

Arundadhi Muthukumar,

Sucila Thangam Ganesan

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Clinical Application of Metabolomics in Infectious Diseases and Future Perspectives DOI
P K BHARTI, Ramesh C. Tripathi, Anshul Singh

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Commercial roadmap of nanobiosensor development DOI Creative Commons
Fulden Ulucan‐Karnak, Cansu İlke Kuru, Sinan Akgöl

и другие.

Frontiers in Nanotechnology, Год журнала: 2024, Номер 6

Опубликована: Фев. 9, 2024

A nanobiosensor is a tool that converts biological stimulus into an electrical output via nanosized transducer elements. Nanobiosensors are promising instruments, especially in biomedical applications the literature and industry. To develop from idea to product, life-cycle approach comprises various processes ranging conception through commercialization required. Developers potential investors should examine market requirements, design possibilities, feasibility, financial return, risk assessments when developing development concept. It critical establish well-defined regulatory pathway for bringing innovation at low cost short period. R&D conduct thorough examinations of nanomaterial toxicity health effects, involving marketing, advertising, analysis. Stakeholders discuss technology transfer office protocols faster, healthier operations.

Язык: Английский

Процитировано

2

Technologies to measure vaccine immune response against infectious diseases DOI

Mahbuba Rahman

Elsevier eBooks, Год журнала: 2024, Номер unknown, С. 75 - 141

Опубликована: Янв. 1, 2024

Процитировано

1