Onkobioloogia loeng genoomikorrashoiu mehhanismidest
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Updated
Dec 4, 2017 - HTML
Onkobioloogia loeng genoomikorrashoiu mehhanismidest
Code for figure generation and analysis in Finding driver mutations in cancer: Elucidating the role of background mutational processes https://doi.org/10.1371/journal.pcbi.1006981
It is a site that shows the activities of the cancer support group Uwezo
Core cancer metabolism model of Palsson et al: https://rdcu.be/Olwc
Analysis of an anti-cancer drug's regimen vs other drug regimens in a mouse study.
analyzing images of mechanical stimulation on low elastic modulus dishes (mSLED)
Cervical Cancer Cell Detection using Image Processing and MATLAB
Predict the effect of genetic mutations in cancer tumors and classify them based on text clinical literature.
Invasive ductal carcinoma (IDC) is - with ~ 80 % of cases - one of the most common types of breast cancer. It's malicious and able to form metastases which makes it especially dangerous.
Code for the article "Cancer cells forgo translating the transcribed genes of non-specialized tasks"
Companion for the 2022 manuscript in Cancer Epidemiology, Biomarkers & Prevention entitled "A National Map of NCI-Designated Cancer Center Catchment Areas on the 50th Anniversary of the Cancer Centers Program"
An implementation of Machine Learning and Data Science on a Breast Cancer study from Memorial Sloan Kettering Cancer Center from 2018. All data was made available on cBioPortal.
This repository contains about my personal project about cancer statistics prediction from 2020
Skin cancer prediction using input values for various parameters from Doctor
In silico identification of CDK1 inhibitors in colorectal cancer
The primary objective of this project is to develop an accurate and efficient predictive model that can classify breast tumors as benign or malignant with a high degree of accuracy. By analyzing the characteristics extracted from mammogram reports, the model will assist healthcare professionals in making timely and informed decisions about patient
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