Introduction to Biomarkers Identification

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10.1136/ANNRHEUMDIS-2021-EULAR.3683

Whole-blood mRNA and plasma proteins were measured in a cohort of biologic naïve r-axSpA|AS patients (n = 35) from the Bioefficacy study (Biomarkers identification of anti-TNF alpha agent efficacy in AS patients using RNA sequencing and mass spectrometry), pre and post (14 weeks) TNFi treatment using adalimumab.

POS0359 MOLECULAR PROFILING OF RADIOGRAPHIC AXIAL SPONDYLOARTHRITIS PATIENTS REVEALS AN ASSOCIATION BETWEEN INNATE AND ADAPTIVE CELL POPULATIONS AND THERAPEUTIC RESPONSE TO ADALIMUMAB

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10.1016/j.gendis.2020.01.013

Here we hypothesize that integrative mining of IR and depression cohort data will facilitate predictive biomarkers identification for T2D.

Insulin-resistance and depression cohort data mining to identify nutraceutical related DNA methylation biomarker for type 2 diabetes

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10.1016/j.mimet.2021.106235

Our results highlight the differences in taxonomic compositions of samples obtained from the two separate pipelines, while underlining the impact on downstream analyses, such as biomarkers identification.

Taxonomic annotation of 16S rRNA sequences of pig intestinal samples using MG-RAST and QIIME2 generated different microbiota compositions.

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10.1007/s41664-021-00197-6

Potential application of glycoproteomics approaches and challenges in biomarkers identification are also discussed.

Mass Spectrometry-based Proteomics and Glycoproteomics in COVID-19 Biomarkers Identification: A Mini-review

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10.1007/s00018-021-03918-3

Metabolomics, along with transcriptomics, has an influential role in discovering connections between genetic regulation, metabolite phenotyping and biomarkers identification.

Metabolomics and health: from nutritional crops and plant-based pharmaceuticals to profiling of human biofluids.

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10.1371/journal.pone.0246668

More reliable and effective biomarkers identification methods are then needed to detect candidate cancer-related genes.

Improved cancer biomarkers identification using network-constrained infinite latent feature selection.

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10.3390/biom11020201

This review aims to provide a comprehensive overview of the state-of-the-art of the new methodologies in cardiac allograft rejection monitoring and investigate the future perspectives on invasive and non-invasive rejection biomarkers identification.

A Changing Paradigm in Heart Transplantation: An Integrative Approach for Invasive and Non-Invasive Allograft Rejection Monitoring

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10.3389/fphar.2021.698671

Last, the results support in-depth studies on nonlethal MeHg concentrations for biomarkers identification that interpret transcriptomics data in toxicological tests serving as an early alert of physiological changes in vitro biological models.

Non-Lethal Concentration of MeHg Causes Marked Responses in the DNA Repair, Integrity, and Replication Pathways in the Exposed Human Salivary Gland Cell Line

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10.1117/12.2536384

This paper describes detailed study of single human platelet and can be used for rapid and early structure changes and biomarkers identification in individuals with cardiovascular decease (CCD) pathology in vitro.

Single human platelet study using surface-enhanced Raman spectroscopy as a perspective tool for antiplatelet therapy effectiveness prediction

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10.1109/ICITEED.2019.8929939

Gene biomarkers identification for diagnosis, prognosis or predictive cancer is challenging work.

Utilizing Gene Co-expression Network for Identifying Subnetwork Biomarkers for Cancer

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10.3760/CMA.J.ISSN.1001-8050.2019.11.014

Objective To analyze the differentially expressed microRNA (miRNA) and their target genes in peripheral blood and bone tissue of postmenopausal osteoporosis (PMOP), and provide basis for the study of pathogenesis as well as biomarkers identification of PMOP.

Differentially expressed microRNA and target gene analysis in patients with postmenopausal osteoporosis

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10.1016/j.foodchem.2018.07.137

A training group of 24 samples and testing group of 21 samples were used to RF classification of biomarkers identification.

Biomarkers-based classification between green teas and decaffeinated green teas using gas chromatography mass spectrometer coupled with in-tube extraction (ITEX).

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10.1158/1538-7445.SABCS18-P5-03-10

Serum exosomes from 40 TNBC stage IV patients underwent chemotherapy before or after progress disease (PD) status were isolated to analyze miRNA profiling for potential biomarkers identification.

Abstract P5-03-10: Circulating exosomal microRNA profiling to depict mechanisms of chemotherapy resistance among triple negative breast cancer

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10.1016/j.pnpbp.2019.03.010

The available studies of metabolomics in Schizophrenia, Bipolar Disorder and Major Depressive Disorder suggest a potential in investigating metabolic pathways involved in these diseases' pathophysiology and response to treatment, as well as its potential in biomarkers identification.

Advances and challenges in development of precision psychiatry through clinical metabolomics on mood and psychotic disorders

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10.1080/10428194.2018.1499905

The study allows better understanding of disease molecular behavior, and it is useful for possible monitoring CML treatment and prognostic biomarkers identification.

Circulating microRNAs expression profile in newly diagnosed and imatinib treated chronic phase – chronic myeloid leukemia

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10.1038/s41598-019-45151-w

The tumor secretome analysis is a promising strategy for biomarkers identification, which can be assessed using transcriptomic data.

Locally advanced rectal cancer transcriptomic-based secretome analysis reveals novel biomarkers useful to identify patients according to neoadjuvant chemoradiotherapy response

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What is/are Biomarkers Identification?

Biomarkers Identification - Whole-blood mRNA and plasma proteins were measured in a cohort of biologic naïve r-axSpA|AS patients (n = 35) from the Bioefficacy study (Biomarkers identification of anti-TNF alpha agent efficacy in AS patients using RNA sequencing and mass spectrometry), pre and post (14 weeks) TNFi treatment using adalimumab. [1] Here we hypothesize that integrative mining of IR and depression cohort data will facilitate predictive biomarkers identification for T2D. [2] Our results highlight the differences in taxonomic compositions of samples obtained from the two separate pipelines, while underlining the impact on downstream analyses, such as biomarkers identification. [3] Potential application of glycoproteomics approaches and challenges in biomarkers identification are also discussed. [4] Metabolomics, along with transcriptomics, has an influential role in discovering connections between genetic regulation, metabolite phenotyping and biomarkers identification. [5] More reliable and effective biomarkers identification methods are then needed to detect candidate cancer-related genes. [6] This review aims to provide a comprehensive overview of the state-of-the-art of the new methodologies in cardiac allograft rejection monitoring and investigate the future perspectives on invasive and non-invasive rejection biomarkers identification. [7] Last, the results support in-depth studies on nonlethal MeHg concentrations for biomarkers identification that interpret transcriptomics data in toxicological tests serving as an early alert of physiological changes in vitro biological models. [8] This paper describes detailed study of single human platelet and can be used for rapid and early structure changes and biomarkers identification in individuals with cardiovascular decease (CCD) pathology in vitro. [9] Gene biomarkers identification for diagnosis, prognosis or predictive cancer is challenging work. [10] Objective To analyze the differentially expressed microRNA (miRNA) and their target genes in peripheral blood and bone tissue of postmenopausal osteoporosis (PMOP), and provide basis for the study of pathogenesis as well as biomarkers identification of PMOP. [11] A training group of 24 samples and testing group of 21 samples were used to RF classification of biomarkers identification. [12] Serum exosomes from 40 TNBC stage IV patients underwent chemotherapy before or after progress disease (PD) status were isolated to analyze miRNA profiling for potential biomarkers identification. [13] The available studies of metabolomics in Schizophrenia, Bipolar Disorder and Major Depressive Disorder suggest a potential in investigating metabolic pathways involved in these diseases' pathophysiology and response to treatment, as well as its potential in biomarkers identification. [14] The study allows better understanding of disease molecular behavior, and it is useful for possible monitoring CML treatment and prognostic biomarkers identification. [15] The tumor secretome analysis is a promising strategy for biomarkers identification, which can be assessed using transcriptomic data. [16]