Mitochondrial dysfunction and oxidative stress in Alzheimer's disease, and Parkinson's disease, Huntington's disease and amyotrophic lateral sclerosis-an updated …
T Alqahtani, SL Deore, AA Kide, BA Shende, R Sharma… - Mitochondrion, 2023 - Elsevier
Misfolded proteins in the central nervous system can induce oxidative damage, which can
contribute to neurodegenerative diseases in the mitochondria. Neurodegenerative patients …
contribute to neurodegenerative diseases in the mitochondria. Neurodegenerative patients …
Translational precision medicine: an industry perspective
In the era of precision medicine, digital technologies and artificial intelligence, drug
discovery and development face unprecedented opportunities for product and business …
discovery and development face unprecedented opportunities for product and business …
Machine learning models for the identification of prognostic and predictive cancer biomarkers: a systematic review
The identification of biomarkers plays a crucial role in personalized medicine, both in the
clinical and research settings. However, the contrast between predictive and prognostic …
clinical and research settings. However, the contrast between predictive and prognostic …
A systematic review on biomarker identification for cancer diagnosis and prognosis in multi-omics: from computational needs to machine learning and deep learning
Biomarkers, also known as biological markers, are substances like transcripts,
deoxyribonucleic acid (DNA), genes, proteins, and metabolites that indicate whether a …
deoxyribonucleic acid (DNA), genes, proteins, and metabolites that indicate whether a …
A random forest based biomarker discovery and power analysis framework for diagnostics research
Background Biomarker identification is one of the major and important goal of functional
genomics and translational medicine studies. Large scale–omics data are increasingly …
genomics and translational medicine studies. Large scale–omics data are increasingly …
Computational techniques and tools for omics data analysis: state-of-the-art, challenges, and future directions
The heterogeneous and high-dimensional nature of omics data presents various challenges
in gaining insights while analysis. In the era of big data, omics data is available as genome …
in gaining insights while analysis. In the era of big data, omics data is available as genome …
Multi-omics profiling approach to asthma: an evolving paradigm
Y Gautam, E Johansson, TB Mersha - Journal of personalized medicine, 2022 - mdpi.com
Asthma is a complex multifactorial and heterogeneous respiratory disease. Although
genetics is a strong risk factor of asthma, external and internal exposures and their …
genetics is a strong risk factor of asthma, external and internal exposures and their …
Machine learning for the advancement of genome-scale metabolic modeling
Constraint-based modeling (CBM) has evolved as the core systems biology tool to map the
interrelations between genotype, phenotype, and external environment. The recent …
interrelations between genotype, phenotype, and external environment. The recent …
Investigation of Genetic Variations of IL6 and IL6R as Potential Prognostic and Pharmacogenetics Biomarkers: Implications for COVID-19 and Neuroinflammatory …
C Strafella, V Caputo, A Termine, S Barati… - Life, 2020 - mdpi.com
In the present study, we investigated the distribution of genetic variations in IL6 and IL6R
genes, which may be employed as prognostic and pharmacogenetic biomarkers for COVID …
genes, which may be employed as prognostic and pharmacogenetic biomarkers for COVID …
Machine learning-driven metabolomic evaluation of cerebrospinal fluid: insights into poor outcomes after aneurysmal subarachnoid hemorrhage
BACKGROUND Aneurysmal subarachnoid hemorrhage (aSAH) is associated with a high
mortality and poor neurologic outcomes. The biologic underpinnings of the morbidity and …
mortality and poor neurologic outcomes. The biologic underpinnings of the morbidity and …