(Q113124839)

English

Multi-Tensor Decompositions for Personalized Cancer Diagnostics and Prognostics

research project

In more languages

default for all languages

No label defined

No description defined

Statements

research project

2 references

https://physics.cancer.gov/research-funding/utah

National Cancer Institute

Wikimedia import URL

https://en.wikipedia.org/wiki/Physical_Sciences-Oncology_Centers

Tensor Generalized Singular Value Decomposition following et int. Alter PLoS One 2015 and Alter NCI Physical Sciences in Oncology 2015.jpg
5,000 × 6,495; 3.05 MB

The tensor generalized singular value decomposition is one of the multi-tensor decompositions, invented to simultaneously identify the similar and dissimilar among, and create a single coherent model from any data types, of any number and dimensions. (English)

0 references

Physical Sciences in Oncology Network

National Cancer Institute

1 reference

https://physics.cancer.gov/research-funding/utah

National Cancer Institute

University of Utah

2 references

https://physics.cancer.gov/research-funding/utah

National Cancer Institute

https://alterlab.org/physics_of_cancer/

multi-tensor decomposition

0 references

2015

1 reference

https://app.dimensions.ai/details/grant/grant.4455012

2023

0 references

subject has role

principal investigator

0 references

Carl T. Wittwer

subject has role

co-investigator

0 references

described at URL

https://alterlab.org/physics_of_cancer/

language of work or name

1 reference

https://physics.cancer.gov/research-funding/utah

National Cancer Institute

described by source

Tensor GSVD of patient- and platform-matched tumor and normal DNA copy-number profiles uncovers chromosome arm-wide patterns of tumor-exclusive platform-consistent alterations encoding for cell transformation and predicting ovarian cancer survival

publication date

April 2015

0 references

DNA Copy-Number Alterations in Primary Ovarian Serous Cystadenocarcinoma Encoding for Cell Transformation and Predicting Survival and Response to Platinum Therapy Throughout the Course of the Disease

publication date

January 2016

0 references

Platform-Independent Genome-Wide Pattern of DNA Copy-Number Alterations Predicting Astrocytoma Survival and Response to Treatment Revealed by the GSVD Formulated as a Comparative Spectral Decomposition

publication date

October 2016

0 references

Patterns of DNA Copy-Number Alterations Revealed by the GSVD and Tensor GSVD Encode for Cell Transformation and Predict Survival and Response to Platinum in Adenocarcinomas

publication date

July 2018

0 references

Mathematically Universal and Biologically Consistent Astrocytoma Genotype Encodes for Transformation and Predicts Survival Phenotype

publication date

July 2018

0 references

Mathematically universal and biologically consistent astrocytoma genotype encodes for transformation and predicts survival phenotype

publication date

September 2018

0 references

GSVD- and tensor GSVD-uncovered patterns of DNA copy-number alterations predict adenocarcinomas survival in general and in response to platinum

publication date

August 2019

0 references

Retrospective clinical trial experimentally validates glioblastoma genome-wide pattern of DNA copy-number alterations predictor of survival

publication date

May 2020

0 references

principal investigator

2 references

https://physics.cancer.gov/research-funding/utah

National Cancer Institute

0000-0002-0418-1078

13 October 2020

Sitelinks

Wikipedia(0 entries)

Wikibooks(0 entries)

Wikinews(0 entries)

Wikiquote(0 entries)

Wikisource(0 entries)

Wikiversity(0 entries)

Wikivoyage(0 entries)

Wiktionary(0 entries)

Multilingual sites(0 entries)

Retrieved from "https://www.wikidata.org/w/index.php?title=Q113124839&oldid=2104281308"