This project is all about a Machine Learning based Medical Test web app which makes predictions about various diseases using the concept of machine learning.

Training and evaluating a variational autoencoder for pan-cancer gene expression data

P-NET, Biologically informed deep neural network for prostate cancer classification and discovery

It was built a web application as a step forward in building a 3D recommendation system.

Backend Server for CIViC Project

Predicting Cell Health with Morphological Profiles

Cross-platform normalization enables machine learning model training on microarray and RNA-seq data simultaneously

Pipeline analysis for whole exome sequencing of pancreatic cancer PDX models

Collection of statistical scripts, image analysis workflows, data used in publications by the Misteli Lab.

Checks if it's s**tpost saturday

Deploying machine learning model using flask

Code repository for macsGESTALT single cell lineage tracing analysis https://doi.org/10.1101/2020.08.11.245787

The current study provides a comprehensive insights into the PDAC metastatic biology.

Analysis for "K27M in canonical and noncanonical H3 variants occurs in distinct oligodendroglial cell lineages in brain midline gliomas" (Jessa et al, Nature Genetics, 2022)

Multi-class KRAS/NRAS Classifier for Multiple Myeloma

An AngularJS frontend for the PanDrugs application

CAP cancer reporting templates

In this assignment, we will tackle a regression problem. We will be working on a dataset consolidated from census data in the USA. The goal is to accurately predict cancer mortality based on information related to US counties.The dataset contains 33 different features (demography, medical information).

A website for spreading awareness against Breast Cancer.