davidenoma Goto Github PK

-team-237-zero-hunger-frontend

active-edge-test

Developer test result

atsea-sample-shop-app

A sample app that uses a Java Spring Boot backend connected to a database to display a fictitious art shop with a React front-end.

bare

bash-oneliner

A collection of handy Bash One-Liners and terminal tricks for data processing and Linux system maintenance.

bioinformaticsfromcoursera

bioinformaticsscripts

A collection of Scripts that solve basic Bioinformatics problems as well as some data science implementations for Bioinformatics.

boltzmann-machines

Boltzmann Machines in TensorFlow with examples

breast-cancer-risk-prediction

Breast cancer risk prediction using genotyped data

c-sharp-codes

cancer-health-disparities-through-genomic-epidemiology-lens

cancer_related_pathways

cancertargetprediction

Code for the manuscript "Genome-wide investigation of gene-cancer associations for the prediction of novel therapeutic targets in oncology"

carrecommendersystem

Recommender system that uses naive bayes classifier to analyse comments on different cars for the sentiments. It employes data mining techniques and an ontology preprocessing to see the effects on the recommendation.

data-science-projects

Collection of programs and scripts in R, Bash and Python to aid the obtaining of insight from data.

datastructuresalgorithm

Data structures and algorithms in python as well as numpy and pandas fundamentals

davidenoma

Config files for my GitHub profile.

dl_geno

driverml

DriverML identifies cancer driver genes. Rigorous and unbiased benchmark analysis and comparisons of DriverML with 20 other existing tools in 31 independent datasets from The Cancer Genome Atlas (TCGA) show that DriverML is robust and powerful among various datasets and outperforms the other tools with a better balance of precision and recall.

emagma-tutorial

A step by step guide on how to use eMAGMA, an approach to conducting eQTL informed gene-based tests.

enhancing-the-capacity-of-variant-effect-prediction-a-multidisciplinary-application

ensemble-learning-gwas

Application of Two Ensemble Learning Methods to GWAS Data

epigwas

Causal inference for interaction detection

explorecali

feat_imp_gwas

featureimportancedl

firstcsharpapp

flashnet

For small jobs naija

geneexpimgtl

TL with CNN for cancer survival prediction using gene-expression data

genstats

Statistics course for JHU Genomic Data Science Sequence