Current Opinion in Plant Biology, Год журнала: 2021, Номер 62, С. 102057 - 102057
Опубликована: Июнь 5, 2021
Язык: Английский
Pharmaceuticals, Год журнала: 2022, Номер 15(5), С. 572 - 572
Опубликована: Май 4, 2022
Natural products have played a critical role in medicine due to their ability bind and modulate cellular targets involved disease. Medicinal plants hold variety of bioactive scaffolds for the treatment multiple disorders. The less adverse effects, affordability, easy accessibility highlight potential traditional remedies. Identifying pharmacological from active ingredients medicinal has become hot topic biomedical research generate innovative therapies. By developing an unprecedented opportunity systematic investigation medicines, network pharmacology is evolving as paradigm becoming frontier field drug discovery development. advancement opened up new avenues understanding complex components found various plants. This study attributed comprehensive summary based on current research, highlighting ingredients, related techniques/tools/databases, development applications. Moreover, this would serve protocol discovering novel compounds explore full range biological traditionally used We attempted cover vast review form. hope it will significant pioneer researchers working with by employing approaches.
Язык: Английский
Процитировано
260
Current Pharmaceutical Analysis, Год журнала: 2023, Номер 19(4), С. 267 - 281
Опубликована: Апрель 11, 2023
Abstract: Multi-omics approaches have developed as a profitable technique for plant systems, popular method in medical and biological sciences underlining the necessity to outline new integrative technology functions facilitate multi-scale depiction of systems. Understanding system through various omics layers reveals supplementary sources variability probably inferring sequence cases leading definitive process. Manuscripts reviews were searched on PubMed with keywords multi-omics, data analysis, omics, integration, deep learning multi-omics integration. Articles that published after 2010 prioritized. The authors focused mainly publications developing approaches. Omics reveal interesting tools produce behavioral interactions microbial communities, integrating details into risk assessment will an impact food safety, also relevant spoilage control procedures. datasets, comprehensively characterizing at molecular level, are continually increasing both dimensionality complexity. analysis is appropriate treatment optimization, testing disease prognosis, achieve mechanistic understandings diseases. New effective solutions together well-designed components recommended many trials. goal this mini-review article introduce technologies considering different analyses.
Язык: Английский
Процитировано
54
npj Science of Food, Год журнала: 2023, Номер 7(1)
Опубликована: Июнь 5, 2023
Abstract The concept of probiotics is witnessing increasing attention due to its benefits in influencing the host microbiome and modulation immunity through strengthening gut barrier stimulation antibodies. These benefits, combined with need for improved nutraceuticals, have resulted extensive characterization leading an outburst data generated using several ‘omics’ technologies. recent development system biology approaches microbial science paving way integrating from different omics techniques understanding flow molecular information one level other clear on regulatory features phenotypes. limitations tendencies a ‘single omics’ application ignore influence processes justify ‘multi-omics’ selections action host. Different techniques, including genomics, transcriptomics, proteomics, metabolomics lipidomics, used studying their are discussed this review. Furthermore, rationale multi-omics integration platforms supporting analyses was also elucidated. This review showed that useful selecting functions microbiome. Hence, recommend approach holistically
Язык: Английский
Процитировано
52
Proteomes, Год журнала: 2023, Номер 11(4), С. 34 - 34
Опубликована: Окт. 20, 2023
Multi-omics is a cutting-edge approach that combines data from different biomolecular levels, such as DNA, RNA, proteins, metabolites, and epigenetic marks, to obtain holistic view of how living systems work interact. has been used for various purposes in biomedical research, identifying new diseases, discovering drugs, personalizing treatments, optimizing therapies. This review summarizes the latest progress challenges multi-omics designing treatments human focusing on integrate analyze multiple proteome examples use multi-proteomics identify drug targets. We also discussed future directions opportunities developing innovative effective therapies by deciphering complexity.
Язык: Английский
Процитировано
50
Scientific Data, Год журнала: 2024, Номер 11(1)
Опубликована: Апрель 11, 2024
Abstract Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, methods exist construct them automatically. However, tackling biomedical problems flexibility way knowledge is modeled. Moreover, existing KG construction provide robust tooling cost fixed or limited choices among representation models. PheKnowLator (Phenotype Translator) a semantic ecosystem for automating FAIR (Findable, Accessible, Interoperable, Reusable) ontologically grounded KGs with fully customizable representation. The includes resources (e.g., preparation APIs), analysis tools SPARQL endpoint abstraction algorithms), benchmarks prebuilt KGs). We evaluated by systematically comparing it open-source analyzing its computational performance when 12 different large-scale KGs. With flexible representation, enables without compromising usability.
Язык: Английский
Процитировано
28
Computational and Structural Biotechnology Journal, Год журнала: 2025, Номер 27, С. 265 - 277
Опубликована: Янв. 1, 2025
Despite the wealth of single-cell multi-omics data, it remains challenging to predict consequences novel genetic and chemical perturbations in human body. It requires knowledge molecular interactions at all biological levels, encompassing disease models humans. Current machine learning methods primarily establish statistical correlations between genotypes phenotypes but struggle identify physiologically significant causal factors, limiting their predictive power. Key challenges modeling include scarcity labeled generalization across different domains, disentangling causation from correlation. In light recent advances data integration, we propose a new artificial intelligence (AI)-powered biology-inspired multi-scale framework tackle these issues. This will integrate organism hierarchies, species genotype-environment-phenotype relationships under various conditions. AI inspired by biology may targets, biomarkers, pharmaceutical agents, personalized medicines for presently unmet medical needs.
Язык: Английский
Процитировано
8
Nucleic Acids Research, Год журнала: 2021, Номер 49(W1), С. W375 - W387
Опубликована: Май 2, 2021
Abstract The Mergeomics web server is a flexible online tool for multi-omics data integration to derive biological pathways, networks, and key drivers important disease pathogenesis based on the open source R package. takes summary statistics of association studies (GWAS, EWAS, TWAS, PWAS, etc.) as input features four functions: Marker Dependency Filtering (MDF) correct known dependency between omics markers, Set Enrichment Analysis (MSEA) detect relevant processes, Meta-MSEA examine consistency processes informed by various datasets, Key Driver (KDA) identify essential regulators disease-associated pathways networks. has been extensively updated streamlined in version 2.0 including an overhauled user interface, improved tutorials results interpretation each analytical step, inclusion numerous GWAS, functional genomics molecular networks allow comprehensive integrations, increased functionality decrease workload, flexibility cater user-specific needs. Finally, we have incorporated our newly developed drug repositioning pipeline PharmOmics prediction potential drugs targeting that were identified Mergeomics. freely accessible at http://mergeomics.research.idre.ucla.edu does not require login.
Язык: Английский
Процитировано
73
Progress in Lipid Research, Год журнала: 2022, Номер 86, С. 101145 - 101145
Опубликована: Янв. 5, 2022
Язык: Английский
Процитировано
58
Microbiological Research, Год журнала: 2022, Номер 265, С. 127180 - 127180
Опубликована: Сен. 6, 2022
Язык: Английский
Процитировано
45
Current Research in Biotechnology, Год журнала: 2022, Номер 4, С. 138 - 151
Опубликована: Янв. 1, 2022
Big data is transforming biomedical research by integrating massive amounts of from laboratory experiments, clinical investigations, healthcare records, and the internet things. Specifically, increasing rate at which information obtained omics technologies (genomics, epigenomics, transcriptomics, proteomics, metabolomics, pharmacogenomics) providing an opportunity for future advances in personalized medicine that are paving way to improved patient care. The recent profoundly contributing big biomedicine anticipated aid disease diagnosis care management. Herein, we critically review major computational techniques, algorithms, their outcomes have contributed generated various complex human diseases, such as cancer infectious diseases. Finally, discuss trends field directions must be considered advance influence on its translation industry.
Язык: Английский
Процитировано
44