MetaOmGraph: a workbench for interactive exploratory data analysis of large expression datasets
-
Updated
May 20, 2022 - Java
MetaOmGraph: a workbench for interactive exploratory data analysis of large expression datasets
Exercises solved for the Practical Statistics Module of Udacity's DAND: assignments and practice problems
Open-source software pipeline for cancer classification from high-throughput data using machine learning.
We used different machine learning approaches to build models for detecting and visualizing important prognostic indicators of breast cancer survival rate. This repository contains R source codes for 5 steps which are, model evaluation, Random Forest further modelling, variable importance, decision tree and survival analysis. These can be a pipe…
Autoencoders - a deep neural network was used for feature extraction followed by clustering of the "Cancer" dataset using k-means technique
A Platypus-based variant calling pipeline for cancer data
A Machine Learning Classifier for Lung & Colon Cancer Histopathological Images.
The first GANs-based omics-to-omics translation framework
Bioconductor R-package: Curated Prostate Cancer Data
An example of predicting breast cancer using existing data to learn with decision trees (scikit-learn/python)
Helping cancer patients find a second opinion anywhere in the US within seconds.
Improving Information Extraction from Pathology Reports using Named Entity Recognition
Examples on processing and working with TCGA mutation and RNA-Seq data
A partir da Cadeira de Introdução a Ciência de Dados (ICD), com o Professor Yuri Malheiros, na Universidade Federal da Paraíba (UFPB), nós, Adriel, Jessica e Kamily, faremos uma analise dos dados estatísticos de casos de câncer, relacionados a certas idades, a fim de responder perguntas pré-definidas.
A comprehensive comparison of decision tree and random forest for cancer classification.
Open-source command-line pipeline for cancer type classification of high-throughput data using machine learning.
In this project I will look at a dataset of patient data relating to breast cancer, and develop a machine learning model that will aim to predict Malignant tumors with the highest accuracy.
Using data from the CDC to track diseases and what might be their causes. Heavily based on data analysis. STILL UNDER CONSTRUCTION!
Targeted and non-targeted anticancer drugs and drug regimens
Add a description, image, and links to the cancer-data topic page so that developers can more easily learn about it.
To associate your repository with the cancer-data topic, visit your repo's landing page and select "manage topics."