About: Integration of multiple types of genetic markers for neuroblastoma may contribute to improved prediction of the overall survival

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scholarly article by Aneta Polewko-Klim et al published 20 September 2018 in Biology Direct

Attributes	Values
rdf:type	Item
description	wetenschappelijk artikel (nl) наукова стаття, опублікована у вересні 2018 (uk) im September 2018 veröffentlichter wissenschaftlicher Artikel (de) scholarly article by Aneta Polewko-Klim et al published 20 September 2018 in Biology Direct (en)
publication date	wds:Q58711964-07393CF1-019D-4F7E-AFF7-516BA3636FFD
publication date	2018-09-20 00:00:00Z (xsd:dateTime)
language of work or name	wds:Q58711964-D3A1C869-901E-429C-8C3C-AA95741D9487
language of work or name	English
exact match	wds:Q58711964-BFCEF62D-4C76-49C9-8D2A-0FE79661CF96
exact match	https://scigraph.springernature.com/pub.10.1186/s13062-018-0222-9
cites work	wds:Q58711964-04D1BD8D-E25F-40F7-8FCB-D8BF9EBB677B wds:Q58711964-066981E5-303C-4AF5-8C36-D426CE64844A wds:Q58711964-0D406B42-FD2C-48A4-ABB7-8086136F2244 wds:Q58711964-0E0B0775-16C8-4907-B711-B939003088B0 wds:Q58711964-101F8626-71F7-4E13-A9A3-177A987D5488 wds:Q58711964-2AC4F392-91BE-40C6-9E37-CC278A526A5D wds:Q58711964-37487439-4250-45E4-9BB5-5ED19EE69C8E wds:Q58711964-392DEE17-30FD-413B-8919-2D94559FD6FE wds:Q58711964-45710B9D-2C61-4C5B-B8E8-5021A54C2968 wds:Q58711964-57AAACC3-BFB8-4C9C-BB2B-71F6974A62A3 wds:Q58711964-5A2C68A3-2C05-44F1-930B-D29647F03E41 wds:Q58711964-6308BA27-9429-43EF-AAD1-447998F1526C wds:Q58711964-6E570B66-BB57-4D38-BC7B-091D8749D937 wds:Q58711964-6E67D207-75AA-4E04-B7A8-BAD7DF68F1BC wds:Q58711964-730F1FBA-55C6-4F82-B34A-A47CFB72FF5E wds:Q58711964-75211B6D-CF46-4B5F-9562-8B1B47A314D5 wds:Q58711964-7A996169-6543-4274-AC4D-25F4613A4136 wds:Q58711964-7B025535-C711-447D-86C0-48D883D6798F wds:Q58711964-7D6CA4A0-D7E9-4E9B-B925-BAC4AB65D2D6 wds:Q58711964-7EED57E0-E18E-49BC-B49C-D69374EE72FC wds:Q58711964-A58A0825-F58B-4306-862E-27731A120801 wds:Q58711964-AFCA633B-2D29-4FE6-B1F8-B7B234B50C76 wds:Q58711964-AFE8F2BE-40CA-41F2-822D-3D269CD34754 wds:Q58711964-BBC64ADE-AD45-4264-896C-43FB721D88FA wds:Q58711964-C636568D-B595-44E5-B4EC-27C002F9E539 wds:Q58711964-C7B64E9E-1C1F-41C3-9D86-F9E3959BFF82 wds:Q58711964-C8FAB4C2-5B93-4082-8819-04DF2AC593BC wds:Q58711964-D385AF59-F61D-4F47-B99E-0229ABD3B6AD wds:Q58711964-E2BF42FC-3A6A-4C4B-A2AF-B419953F6A64 wds:Q58711964-F211C4E4-3134-4069-B7B0-79737D533365 wds:Q58711964-FB8FB3B1-A62E-4244-AA25-DDFAAEA4B809 wds:Q58711964-FBE551C0-3E3A-47C8-B2E7-F4BFBD0C262E wds:Q58711964-FE62B095-5BD5-4C50-8EFE-30DEADE6CD34
cites work	Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy Comparison of RNA-seq and microarray-based models for clinical endpoint prediction A forest-based approach to identifying gene and gene gene interactions. AceView: a comprehensive cDNA-supported gene and transcripts annotation Evaluation of different biological data and computational classification methods for use in protein interaction prediction Gene selection and classification of microarray data using random forest. Clinical significance of tumor-associated inflammatory cells in metastatic neuroblastoma The double-histone-acetyltransferase complex ATAC is essential for mammalian development Comparison of the predicted and observed secondary structure of T4 phage lysozyme Orchestrating high-throughput genomic analysis with Bioconductor Random forests for genetic association studies. INTERSNP: genome-wide interaction analysis guided by a priori information A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification Human QKI, a potential regulator of mRNA expression of human oligodendrocyte-related genes involved in schizophrenia Genome-wide pathway analysis in neuroblastoma Predicting protein-protein interactions from primary protein sequences using a novel multi-scale local feature representation scheme and the random forest Capturing heterogeneity in gene expression studies by surrogate variable analysis High genomic instability predicts survival in metastatic high-risk neuroblastoma Age-dependent accumulation of genomic aberrations and deregulation of cell cycle and telomerase genes in metastatic neuroblastoma. Pleckstrin-2 selectively interacts with phosphatidylinositol 3-kinase lipid products and regulates actin organization and cell spreading Hox-C9 activates the intrinsic pathway of apoptosis and is associated with spontaneous regression in neuroblastoma The zinc finger proteins ZNF644 and WIZ regulate the G9a/GLP complex for gene repression Exploiting SNP correlations within random forest for genome-wide association studies Recent biologic and genetic advances in neuroblastoma: Implications for diagnostic, risk stratification, and treatment strategies Robustness of Random Forest-based gene selection methods. Neuroblastoma treatment in the post-genomic era. Chromosome 17/17q gain and unaltered profiles in high resolution array-CGH are prognostically informative in neuroblastoma. One-Sided Confidence Contours for Probability Distribution Functions Ten quick tips for machine learning in computational biology. p28, a novel ERGIC/cis Golgi protein, required for Golgi ribbon formation Identification of potential tissue-specific cancer biomarkers and development of cancer versus normal genomic classifiers. An in vivo screening system to identify tumorigenic genes
author name string	wds:Q58711964-24B9EF71-251C-43CE-A359-3EE51CE41A15 wds:Q58711964-46668C04-3C88-4F33-8F82-987DBE5CF063
author name string	Krzysztof Mnich Radosław Piliszek
rdfs:label	Integration of multiple types of genetic markers for neuroblastoma may contribute to improved prediction of the overall survival (en) Integration of multiple types of genetic markers for neuroblastoma may contribute to improved prediction of the overall survival (nl)
skos:prefLabel	Integration of multiple types of genetic markers for neuroblastoma may contribute to improved prediction of the overall survival (en) Integration of multiple types of genetic markers for neuroblastoma may contribute to improved prediction of the overall survival (nl)
name	Integration of multiple types of genetic markers for neuroblastoma may contribute to improved prediction of the overall survival (en) Integration of multiple types of genetic markers for neuroblastoma may contribute to improved prediction of the overall survival (nl)
author	wds:Q58711964-047833DB-3045-47D9-8CD5-529E3152DA66 wds:Q58711964-20AD526E-DC33-4922-A782-7DE4F376619F wds:Q58711964-77F8B30A-7D87-4E1B-B72A-3C3CFE3E3081
author	Witold R Rudnicki Aneta Polewko-Klim Wojciech Lesiński
title	wds:Q58711964-FB3BC538-B34D-4BBA-B16E-75EE93F9137B
title	Integration of multiple types of genetic markers for neuroblastoma may contribute to improved prediction of the overall survival (en)
page(s)	wds:Q58711964-BCC41011-595F-4987-87E2-F1CEF02E1938
page(s)	17
instance of	wds:Q58711964-992EC1AC-4173-4FBE-AED8-E7F91787103C
instance of	scholarly article
main subject	wds:Q58711964-246191CC-DE3A-4FAC-B0DC-AE0BA6429D14

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