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An assessment of potential epitopes in SARS-CoV-2 structural proteins

Researchers utilized multiple bioinformatics resources to identify potent T- and B-cell epitopes of four SARS-CoV-2 structural proteins. ....

Middle East , Coronavirus Disease Covid 19 , Ars Cov 2 , Immune Response , Ers Cov , Respiratory Disease , Evere Acute Respiratory , Evere Acute Respiratory Syndrome , T Cell ,

Vaping linked to dysregulation of mitochondrial genes and immune response genes

Since they hit the market, e-cigarettes have been touted as a safe alternative to tobacco cigarettes for adult smokers. ....

Ahmad Besaratinia , Emily Henderson , Centers For Disease , Keck School Of Medicine , Keck School , Scientific Reports , Disease Control , Immune Response , Public Health ,

Singapore researchers develop ultra-sensitive 2D material sensor to detect breast cancer cells

Cells can produce unique electrical signals. These signals can be linked to various cancers, such as the breast, lung, liver, brain, pancreas and prostate cancers, meaning that they can be used as indicators for early cancer diagnosis. ....

Natasa Bajalovic , Denise Lee , Lunna Li , Desmond Loke , Sophia Chan , Maria Meivita , Emily Henderson , Bioinformatics Institute , Yaw Sing Tan , Breast Cancer , Cancer Diagnosis , Cell Membrane ,

"Systematic evaluation of machine learning methods for identifying huma" by Huaming Chen, Fuyi Li et al.

In recent years, high-throughput experimental techniques have significantly enhanced the accuracy and coverage of protein-protein interaction identification, including human-pathogen protein-protein interactions (HP-PPIs). Despite this progress, experimental methods are, in general, expensive in terms of both time and labour costs, especially considering that there are enormous amounts of potential protein-interacting partners. Developing computational methods to predict interactions between human and bacteria pathogen has thus become critical and meaningful, in both facilitating the detection of interactions and mining incomplete interaction maps. In this paper, we present a systematic evaluation of machine learning-based computational methods for human-bacterium protein-protein interactions (HB-PPIs). We first reviewed a vast number of publicly available databases of HP-PPIs and then critically evaluate the availability of these databases. Benefitting from its well-structured nature, ....

Uman Pathogen Interactions , Machine Learning , Rotein Protein Interactions , Sequential Analysis , Systematic Evaluation ,

"Towards Building a Quantitative Proteomics Toolbox in Precision Medici" by Alejandro Correa Rojo, Dries Heylen et al.

Precision medicine as a framework for disease diagnosis, treatment, and prevention at the molecular level has entered clinical practice. From the start, genetics has been an indispensable tool to understand and stratify the biology of chronic and complex diseases in precision medicine. However, with the advances in biomedical and omics technologies, quantitative proteomics is emerging as a powerful technology complementing genetics. Quantitative proteomics provide insight about the dynamic behaviour of proteins as they represent intermediate phenotypes. They provide direct biological insights into physiological patterns, while genetics accounting for baseline characteristics. Additionally, it opens a wide range of applications in clinical diagnostics, treatment stratification, and drug discovery. In this mini-review, we discuss the current status of quantitative proteomics in precision medicine including the available technologies and common methods to analyze quantitative proteomics d ....

Biomarker Discovery , Clinical Diagnostics , Precision Medicine , Rotein Quantitative Trait Loci , Quantitative Proteomics , Argeted Techniques ,