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Redirected from Oncogenomics
Cancer genomics (Oncogenomics, 암유전체학) is a relatively new sub-field of Genomics that applies high throughput technologies to characterize genes associated with Cancer. (http://en.wikipedia.org/wiki/Oncogenomics)
Table of Contents
관련 정보 #
기사 #
리소스 #
논문 #
- The use of technical replication for detection of low-level somatic mutations in next-generation sequencing Nature Communications : 낮은 빈도의 변이를 NGS 자료에서 찾기 위해 반복실험을 잘 이용하는 방법. 김상우 교수 연구팀 보고.
- 관련기사 - 1% 미세돌연변이까지 찾아내는 유전자 분석기술 개발
- Integrative omics analyses broaden treatment targets in human cancer : Database of Evidence for Precision Oncology (DEPO) 를 이용한 암 마커 탐색
- A pathology atlas of the human cancer transcriptome Science
- Bioinformatics Data Analysis of Next-Generation Sequencing Data from Heterogeneous Tumor Samples Methods Molecular Biology : Heterogeneous 암 샘플에서 NGS 분석하기
- Tissue-specific tumorigenesis: context matters Nature Reviews Cancer : 암종별 잦은 유전변이에 대한 체계적 리뷰, COSMIC 기반.
- Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer : A Joint Consensus Recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists The Journal of Molecular Diagnostics : NGS로 암 유전변이 확인에 관한 표준화 - 4 tiered system 제안
- tier I, variants with strong clinical significance
- tier II, variants with potential clinical significance
- tier III, variants of unknown clinical significance
- tier IV, variants deemed benign or lkely benign
- Current practices and guidelines for clinical next-generation sequencing oncology testing Cancer Biology & Medicine
- End of cancer-genome project prompts rethink Nature : TCGA 암유전체 프로젝트가 대부분 종료됨. 더 해야하나?
- Cancer genomics: from discovery science to personalized medicine Nature Medicine
- The cancer genome Nature
포스트 #
- Simple consensus approach improves somatic mutation prediction accuracy 단맛만좋아요 : Somatic mutation call 방법과 validation
Incoming Links #
[Medical Scholarly Articles] About (MedicalScholarlyArticle 0) #
- A framework for organizing cancer-related variations from existing databases, publications and NGS data using a High-performance Integrated Virtual Environment (HIVE)
- Cancer genomics: from discovery science to personalized medicine
- Cancer-specific defects in DNA repair pathways as targets for personalized therapeutic approaches
- Comprehensive molecular portraits of human breast tumours
- Identification of cancer-driver genes in focal genomic alterations from whole genome sequencing data
- Landscape of somatic mutations in 560 breast cancer whole-genome sequences
- Pathway and network analysis of cancer genomes
- Patterns of somatic mutation in human cancer genomes
- The cancer genome
- The landscape of somatic copy-number alteration across human cancers
- The life history of 21 breast cancers
- The topography of mutational processes in breast cancer genomes
[Codes] About (Code 1) #
Related Software Applications (SoftwareApplication 2) #
Related People (Person 3) #
[Web Applications] About (WebApplication 4) #
Related Articles (Article 5) #
[Datasets] About (Dataset 6) #
- CIViC
- GENIE
- GENT
- Genomic Data Commons
- Genomics of Drug Sensitivity in Cancer
- ICGC
- My Cancer Genome
- TARGET
- TCGA
- Tumorscape
[Web Pages] About (WebPage 7) #
[Software Applications] About (SoftwareApplication 8) #
Related Web Applications (WebApplication 9) #
Suggested Pages #
- 0.135 BioMart
- 0.116 Machine learning for Genomics
- 0.096 Syndecan-2
- 0.075 GDISC
- 0.062 VarScan 2: Somatic mutation and copy number alteration discovery in cancer by exome sequencing
- 0.054 Drug response
- 0.041 Liver cancer
- 0.034 Colorectal cancer
- 0.030 Identification of druggable cancer driver genes amplified across TCGA datasets
- 0.025 Bioinformatics
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