Matches in SemOpenAlex for { <https://semopenalex.org/work/W3013640851> ?p ?o ?g. }
Showing items 1 to 71 of
71
with 100 items per page.
- W3013640851 endingPage "276" @default.
- W3013640851 startingPage "258" @default.
- W3013640851 abstract "The post-genomic era consists of experimental and computational efforts to meet the challenge of clarifying and understanding the function of genes and their products. Proteomic studies play a key role in this endeavour by complementing other functional genomics approaches, encompasses the large-scale analysis of complex mixtures, including the identification and quantification of proteins expressed under different conditions, the determination of their properties, modifications and functions. Understanding how biological processes are regulated at the protein level is crucial to understanding the molecular basis of diseases and often highlights the prevention, diagnosis and treatment of diseases. High-throughput technologies are widely used in proteomics to perform the analysis of thousands of proteins. Specifically, mass spectrometry (MS) is an analytical technique for characterizing biological samples and is increasingly used in protein studies because of its targeted, nontargeted, and high performance abilities. However, as large data sets are created, computational methods such as data mining techniques are required to analyze and interpret the relevant data. More specifically, the application of data mining techniques in large proteomic data sets can assist in many interpretations of data; it can reveal protein-protein interactions, improve protein identification, evaluate the experimental methods used and facilitate the diagnosis and biomarker discovery. With the rapid advances in mass spectrometry devices and experimental methodologies, MS-based proteomics has become a reliable and necessary tool for elucidating biological processes at the protein level. Over the past decade, we have witnessed a great expansion of our knowledge of human diseases with the adoption of proteomic technologies based on MS, which leads to many interesting discoveries. Here, we review recent advances of data mining in MS-based proteomics in biomedical research. Recent research in many fields shows that proteomics goes beyond the simple classification of proteins in biological systems and finally reaches its initial potential – as an essential tool to aid related disciplines, notably biomedical research. From here, there is great potential for data mining in MS-based proteomics to move beyond basic research, into clinical research and diagnostics." @default.
- W3013640851 created "2020-04-03" @default.
- W3013640851 creator A5003806532 @default.
- W3013640851 creator A5035168530 @default.
- W3013640851 creator A5071508921 @default.
- W3013640851 date "2020-03-24" @default.
- W3013640851 modified "2023-09-23" @default.
- W3013640851 title "Data mining in mass spectrometry-based proteomics studies" @default.
- W3013640851 doi "https://doi.org/10.32508/stdjet.v2i4.483" @default.
- W3013640851 hasPublicationYear "2020" @default.
- W3013640851 type Work @default.
- W3013640851 sameAs 3013640851 @default.
- W3013640851 citedByCount "0" @default.
- W3013640851 crossrefType "journal-article" @default.
- W3013640851 hasAuthorship W3013640851A5003806532 @default.
- W3013640851 hasAuthorship W3013640851A5035168530 @default.
- W3013640851 hasAuthorship W3013640851A5071508921 @default.
- W3013640851 hasBestOaLocation W30136408511 @default.
- W3013640851 hasConcept C104317684 @default.
- W3013640851 hasConcept C116834253 @default.
- W3013640851 hasConcept C124101348 @default.
- W3013640851 hasConcept C124535831 @default.
- W3013640851 hasConcept C14036430 @default.
- W3013640851 hasConcept C141231307 @default.
- W3013640851 hasConcept C189206191 @default.
- W3013640851 hasConcept C2522767166 @default.
- W3013640851 hasConcept C41008148 @default.
- W3013640851 hasConcept C46111723 @default.
- W3013640851 hasConcept C55493867 @default.
- W3013640851 hasConcept C59822182 @default.
- W3013640851 hasConcept C60644358 @default.
- W3013640851 hasConcept C70721500 @default.
- W3013640851 hasConcept C78458016 @default.
- W3013640851 hasConcept C86803240 @default.
- W3013640851 hasConceptScore W3013640851C104317684 @default.
- W3013640851 hasConceptScore W3013640851C116834253 @default.
- W3013640851 hasConceptScore W3013640851C124101348 @default.
- W3013640851 hasConceptScore W3013640851C124535831 @default.
- W3013640851 hasConceptScore W3013640851C14036430 @default.
- W3013640851 hasConceptScore W3013640851C141231307 @default.
- W3013640851 hasConceptScore W3013640851C189206191 @default.
- W3013640851 hasConceptScore W3013640851C2522767166 @default.
- W3013640851 hasConceptScore W3013640851C41008148 @default.
- W3013640851 hasConceptScore W3013640851C46111723 @default.
- W3013640851 hasConceptScore W3013640851C55493867 @default.
- W3013640851 hasConceptScore W3013640851C59822182 @default.
- W3013640851 hasConceptScore W3013640851C60644358 @default.
- W3013640851 hasConceptScore W3013640851C70721500 @default.
- W3013640851 hasConceptScore W3013640851C78458016 @default.
- W3013640851 hasConceptScore W3013640851C86803240 @default.
- W3013640851 hasIssue "4" @default.
- W3013640851 hasLocation W30136408511 @default.
- W3013640851 hasOpenAccess W3013640851 @default.
- W3013640851 hasPrimaryLocation W30136408511 @default.
- W3013640851 hasRelatedWork W1885916946 @default.
- W3013640851 hasRelatedWork W1967490900 @default.
- W3013640851 hasRelatedWork W2010715465 @default.
- W3013640851 hasRelatedWork W2020272686 @default.
- W3013640851 hasRelatedWork W2035719588 @default.
- W3013640851 hasRelatedWork W2114484480 @default.
- W3013640851 hasRelatedWork W2395805925 @default.
- W3013640851 hasRelatedWork W2489887948 @default.
- W3013640851 hasRelatedWork W2759363431 @default.
- W3013640851 hasRelatedWork W2808428344 @default.
- W3013640851 hasVolume "2" @default.
- W3013640851 isParatext "false" @default.
- W3013640851 isRetracted "false" @default.
- W3013640851 magId "3013640851" @default.
- W3013640851 workType "article" @default.