About: Pathway and Network Approaches for Identification of Cancer Signature Markers from Omics Data

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Pathway and Network Approaches for Identification of Cancer Signature Markers from Omics Data
Creator	Avital, Itzhak Liu, Meng Stojadinovic, Alexander Wang, Jinlian Yang, Xiaowei Zuo, Yiming Man, Yan-Gao Ressom, Habtom Tadesse, Mahlet Varghese, Rency
Source	PMC
abstract	The advancement of high throughput omic technologies during the past few years has made it possible to perform many complex assays in a much shorter time than the traditional approaches. The rapid accumulation and wide availability of omic data generated by these technologies offer great opportunities to unravel disease mechanisms, but also presents significant challenges to extract knowledge from such massive data and to evaluate the findings. To address these challenges, a number of pathway and network based approaches have been introduced. This review article evaluates these methods and discusses their application in cancer biomarker discovery using hepatocellular carcinoma (HCC) as an example.
has issue date	2015-01-01(xsd:dateTime)
bibo:doi	10.7150/jca.10631
bibo:pmid	25553089
has license	cc-by-nc-nd
sha1sum (hex)	3b5c43f1068e79db27adaca5df0bd717851c37cc
schema:url	https://doi.org/10.7150/jca.10631
resource representing a document's title	Pathway and Network Approaches for Identification of Cancer Signature Markers from Omics Data
has PubMed Central identifier	PMC4278915
has PubMed identifier	25553089
schema:publication	J Cancer
resource representing a document's body	covid:3b5c43f1068e79db27adaca5df0bd717851c37cc#body_text
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