Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information

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Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information

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High-throughput technology allows for genome-wide measurements at different molecular levels for the same patient, e.g. single nucleotide polymorphisms (SNPs) and gene expression. Correspondingly, it might be beneficial to also integrate complementary information from different molecular levels when building multivariable risk prediction models for a clinical endpoint, such as treatment response or survival. |

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Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information

**Báo cáo khoa học: "INTEGRATING MULTIPLE KNOWLEDGE SOURCES FOR DETECTION AND CORRECTION OF REPAIRS IN HUMAN-COMPUTER DIALOG*"**

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Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information

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Đang chuẩn bị liên kết để tải về tài liệu: Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information

Báo cáo khoa học: "INTEGRATING MULTIPLE KNOWLEDGE SOURCES FOR DETECTION AND CORRECTION OF REPAIRS IN HUMAN-COMPUTER DIALOG*"

Báo cáo khoa học: "Integrating Multiple Knowledge Sources to Disambiguate Word Sense: An Exemplar-Based Approach"

Doctor of Philosophy thesis in theory and methodology of English language teaching: Integrating multiple intelligences-based activities into teaching speaking skills to EFL learners

Chương 14: Integrating multiple system views

Báo cáo y học: "Integrating phenotype ontologies across multiple specie"

Working pAper series no 1041/ A pril 2009: An economic cApitAl model integrAting credit And interest rAte risk in the bAnking book

BASICS OF MECHANICAL ENGINEERING: INTEGRATING SCIENCE, TECHNOLOGY AND COMMON SENSE

A NMF based approach for integrating multiple data sources to predict HIV-1–human PPIs

Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information

Integrating gene set analysis and nonlinear predictive modeling of disease phenotypes using a Bayesian multitask formulation

Đang chuẩn bị liên kết để tải về tài liệu:
Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information

**Báo cáo khoa học: "INTEGRATING MULTIPLE KNOWLEDGE SOURCES FOR DETECTION AND CORRECTION OF REPAIRS IN HUMAN-COMPUTER DIALOG*"**