Results 11 to 20 of about 146,987 (295)
Cancer Discovery, 2012 Abstract A comprehensive molecular analysis of tumor samples from 825 patients with breast cancer, conducted through The Cancer Genome Atlas, suggests new approaches to therapy.
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Chromoanagenesis landscape in 10,000 TCGA patients [PDF]
Cancers, 2021 AbstractDuring the past decade, whole-genome sequencing of tumor biopsies and individuals with congenital disorders highlighted the phenomenon of chromoanagenesis, a single chaotic event of chromosomal rearrangement. Chromoanagenesis was shown to be frequent in many types of cancers, to occur in early stages of cancer development, and significantly ...
Roni Rasnic, Michal Linial
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Morphometic analysis of TCGA glioblastoma multiforme [PDF]
BMC Bioinformatics, 2011 AbstractBackgroundOur goals are to develop a computational histopathology pipeline for characterizing tumor types that are being generated by The Cancer Genome Atlas (TCGA) for genomic association. TCGA is a national collaborative program where different tumor types are being collected, and each tumor is being characterized using a variety of genome ...
Chang, Hang +7 more
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TCGA-Assembler: open-source software for retrieving and processing TCGA data [PDF]
Nature Methods, 2014 To the Editor: The Cancer Genome Atlas (TCGA) has been generating multi-modal genomics, epigenomics, and proteomics data for thousands of tumor samples across more than 20 types of cancer. While the access to most level-1 and -2 TCGA data is restricted, the entire level-3 TCGA data as well as some level-1 clinical data (e.g., survival and drug ...
Yitan, Zhu, Peng, Qiu, Yuan, Ji
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TCGA-assembler 2: software pipeline for retrieval and processing of TCGA/CPTAC data [PDF]
Bioinformatics, 2017 Abstract Motivation The Cancer Genome Atlas (TCGA) program has produced huge amounts of cancer genomics data providing unprecedented opportunities for research. In 2014, we developed TCGA-Assembler, a software pipeline for retrieval and processing of public TCGA data.
Lin Wei +5 more
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Machine learning analysis of TCGA cancer data
PeerJ Computer Science, 2021 In recent years, machine learning (ML) researchers have changed their focus towards biological problems that are difficult to analyse with standard approaches. Large initiatives such as The Cancer Genome Atlas (TCGA) have allowed the use of omic data for the training of these algorithms.
Jose Liñares-Blanco +2 more
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Journal of Virology, 2015 ABSTRACT Next-generation sequencing results obtained to detect somatic mutations in human cancers can also be searched for viruses that contribute to cancer. Recently, human papillomavirus 18 RNA was detected in tumor types not typically associated with HPV infection.
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SnapShot: TCGA-Analyzed Tumors
Cell, 2018 This SnapShot provides a list of the tumor types characterized by The Cancer Genome Atlas (TCGA) program. Key findings shown are the most relevant discoveries described in each marker paper for the tumor type.
Amy, Blum +2 more
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TCGA Expedition: A Data Acquisition and Management System for TCGA Data
PLOS ONE, 2016 The Cancer Genome Atlas Project (TCGA) is a National Cancer Institute effort to profile at least 500 cases of 20 different tumor types using genomic platforms and to make these data, both raw and processed, available to all researchers. TCGA data are currently over 1.2 Petabyte in size and include whole genome sequence (WGS), whole exome sequence ...
Uma R Chandran +14 more
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Biotechnology & Biotechnological Equipment, 2021 Bladder cancer (BLCA) is a common malignancy and has a poor prognosis. Single nucleotide polymorphisms (SNPs) in genes are closely associated with the tumorigenesis and tumor development and yet are not well illustrated in BLCA.
Tengyun Long +6 more
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