2015
DOI: 10.1007/978-94-007-7681-4_14
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OMICS for Tumor Biomarker Research

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Cited by 5 publications
(3 citation statements)
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“…The first systemic development of “-omics” science in Russia started in the early 2000s at the Institute of Biomedical Chemistry (IBMC) in Moscow. By that time, IBMC, dealing with problems of biological and medical chemistry under the leadership of academician of the Russian Academy of Sciences (RAS) Alexsander I. Archakov, was actively developing post-genomic technologies, such as transcriptomics and proteomics [ 7 , 8 , 9 , 10 , 11 , 12 , 13 ]. In 2000, the first in the country Department of Proteomic Research and, in 2003, the “Human proteome” Core Facility was created at IBMC.…”
Section: Metabolomics In Russiamentioning
confidence: 99%
See 1 more Smart Citation
“…The first systemic development of “-omics” science in Russia started in the early 2000s at the Institute of Biomedical Chemistry (IBMC) in Moscow. By that time, IBMC, dealing with problems of biological and medical chemistry under the leadership of academician of the Russian Academy of Sciences (RAS) Alexsander I. Archakov, was actively developing post-genomic technologies, such as transcriptomics and proteomics [ 7 , 8 , 9 , 10 , 11 , 12 , 13 ]. In 2000, the first in the country Department of Proteomic Research and, in 2003, the “Human proteome” Core Facility was created at IBMC.…”
Section: Metabolomics In Russiamentioning
confidence: 99%
“…With continuous optimization and improvement of high-tech research methods, metabolomics has become a wide area for the use of “-omics” technologies for medical purposes, the results of which are promising for future implementation [ 12 , 68 , 69 ]. With the support of the National Cancer Institute (NCI), Food and Drug Administration (FDA), and others, the Institute of Medicine (IOM) has been called upon to define the criteria and procedures for assessing the validity of tests created for the clinic.…”
Section: Current Trends In Metabolomicsmentioning
confidence: 99%
“…A high dimensionality of the data in relation to small numbers of available samples (often referred to as the p >> n problem), influences of additive and multiplicative noise, large numbers of uninformative or redundant data features, outliers, confounding factors and imbalanced sample group numbers are all common characteristics of current biomedical data collections. While first successes have been achieved in developing clinical decision support tools using multifactorial omics data, e.g., resulting in FDA-approved omics-based biomarker signatures for common cancer indications [ 1 ], there is still an unmet need and great potential for earlier, more accurate and robust diagnostic and prognostic tools for many complex diseases.…”
Section: Introductionmentioning
confidence: 99%