PXD019653

PXD019653 is an original dataset announced via ProteomeXchange.

Title	Cancer tissue classication using machine learning applied to MALDI MSI and high resolution H&E stained images
Description	To identify a panel of m/z markers for the early detection of colorectal cancer (CRC). Identication of a molecular pattern that can distinguish the primary tumours of colorectal cancer with lymph node metastasis compared to those without. Using MALDI MSI data,we developed and validated a machine learning model that can be used for early screening of CRC. Our model yields high sensitivity and specicity in distinguishing normal tissue from the cancerous. Model described here, can be a used in clinical labs for early diagnosis of colorectal cancer.
HostingRepository	PRIDE
AnnounceDate	2022-02-15
AnnouncementXML	Submission_2022-02-15_13:08:30.040.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Parul Mittal
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	No PTMs are included in the dataset
Instrument	ultraflex

Revision	Datetime	Status	ChangeLog Entry
0	2020-06-08 07:45:46	ID requested
⏵ 1	2022-02-15 13:08:31	announced

Mittal P, Condina MR, Klingler-Hoffmann M, Kaur G, Oehler MK, Sieber OM, Palmieri M, Kommoss S, Brucker S, McDonnell MD, Hoffmann P, Cancer Tissue Classification Using Supervised Machine Learning Applied to MALDI Mass Spectrometry Imaging. Cancers (Basel), 13(21):(2021) [pubmed]

submitter keyword: CRC Colorectal cancer Machine learning MALDI MSI Matrix assisted laser desorption/ionisation mass spectrometry imaging

Prof Peter Hoffmann
contact affiliation	Strand Leader and Lloyd Sansom Chair Biomaterials Engineering and Nanomedicine Future Industries Institute I Building X – X1-10 Mawson Lakes Campus I GPO Box 2471
contact email	peter.hoffmann@unisa.edu.au
lab head
Parul Mittal
contact affiliation	Research associate
contact email	pearl106@gmail.com
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2022/02/PXD019653

PRIDE project URI

• PRIDE
  1. PXD019653
     1. Label: PRIDE project
     2. Name: Cancer tissue classication using machine learning applied to MALDI MSI and high resolution H&E stained images