OpenSourceCancer/cancer-bayes
Predicting breast cancer at 97.51% accuracy with Naive Bayes Classifier for learning purposes.
Discovered public repositories for OpenSourceCancer in the GitHub catalog.
Predicting breast cancer at 97.51% accuracy with Naive Bayes Classifier for learning purposes.
Software for manipulating and visualizing Complete Genomics data, with a focus on cancer
R package providing various functions relevant for gene expression analysis with emphasis on breast cancer.
An online cancer expression analysis tool
A cancer cell simulation
franklin library for NGS sequencing analysis.
This is a cancer knowledge base system
A program that uses the k nearest neighbor algorithm and training data to predict whether cancer is malignant or benign
Public repository.
Cancer Knowledge based system is used for diagnosis of various types of cancers and getting information on supported types of cancers. It currently supports 10 types of common cancers suspected to be among the major types.
This package contains a set of functions related to network inference combining genomic data and prior information extracted from biomedical literature and structured biological databases.The main function is able to generate networks using bayesian or regression-based inference methods; while the former is limited to < 100 of variables, the latter may infer network with hundreds of variables. Several statistics at the edge and node levels have been implemented (edge stability, predictive ability of each node, ...) in order to help the user to focus on high quality subnetworks. Ultimately, this package is used in the 'Predictive Networks' web application developed by the Dana-Farber Cancer Institute in collaboration with Entagen
Kitchen sink of Java/Groovy classes for UCSC cancer genomics.
CloudBioLinux: configure virtual (or real) machines with tools for biological analyses
Official git repository for Biopython (converted from CVS)
lung cancer detection project