PROTEIN EXPRESSION ANALYSIS FOR DOWN SYNDROME

Overview

PROTEIN-EXPRESSION-ANALYSIS-FOR-DOWN-SYNDROME

Down syndrome (DS) is a chromosomal disorder where organisms have an extra chromosome 21, sometimes known as trisomy 21. Being a syndrome, DS consists of multiple symptoms affecting a large number of systems in the body. It’s effect on learning results in it being an intellectual disability . Memantine is currently proposed as a treatment of the learning deficit symptoms in DS. In this project, we have used several supervised machine learning methods:logistic regression, a random forest classifier,k nearest neighbour and voting classifier, to identify which protein(s) are critical to mice learning ability after being exposed to context fear conditioning (CFC). 77 protein expression levels are analysed from both control and trisomic (Ts65Dn) genotype mice, both with and without treatment from the drug memantine. Results suggest that voting classification approach can identify the most important proteins which may help to identify more effective drugs to help the learning process in people with DS.

Identified proteins critical to learning ability and classification of mice based on protein expression values using machine learning algorithms.

Tutorial for Decision Threshold In Machine Learning.

Decision-Threshold-ML Tutorial for improve skills: 'Decision Threshold In Machine Learning' (from GeeksforGeeks) by Marcus Mariano For more informatio

0 Jan 20, 2022
This jupyter notebook project was completed by me and my friend using the dataset from Kaggle

ARM This jupyter notebook project was completed by me and my friend using the dataset from Kaggle. The world Happiness 2017, which ranks 155 countries

1 Jan 23, 2022
This repository contains full machine learning pipeline of the Zillow Houses competition on Kaggle platform.

Zillow-Houses This repository contains full machine learning pipeline of the Zillow Houses competition on Kaggle platform. Pipeline is consists of 10

2 Jan 09, 2022
Covid-polygraph - a set of Machine Learning-driven fact-checking tools

Covid-polygraph, a set of Machine Learning-driven fact-checking tools that aim to address the issue of misleading information related to COVID-19.

1 Apr 22, 2022
Quantum Machine Learning

The Machine Learning package simply contains sample datasets at present. It has some classification algorithms such as QSVM and VQC (Variational Quantum Classifier), where this data can be used for e

Qiskit 364 Jan 08, 2023
nn-Meter is a novel and efficient system to accurately predict the inference latency of DNN models on diverse edge devices

A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

Microsoft 241 Dec 26, 2022
ArviZ is a Python package for exploratory analysis of Bayesian models

ArviZ (pronounced "AR-vees") is a Python package for exploratory analysis of Bayesian models. Includes functions for posterior analysis, data storage, model checking, comparison and diagnostics

ArviZ 1.3k Jan 05, 2023
Simplify stop motion animation with machine learning.

Simplify stop motion animation with machine learning.

Nick Bild 25 Sep 15, 2022
Forecasting prices using Facebook/Meta's Prophet model

CryptoForecasting using Machine and Deep learning (Part 1) CryptoForecasting using Machine Learning The main aspect of predicting the stock-related da

1 Nov 27, 2021
Reggy - Regressions with arbitrarily complex regularization terms

reggy Regressions with arbitrarily complex regularization terms. Currently suppo

Kim 1 Jan 20, 2022
Land Cover Classification Random Forest

You can perform Land Cover Classification on Satellite Images using Random Forest and visualize the result using Earthpy package. Make sure to install the required packages and such as

Dr. Sander Ali Khowaja 1 Jan 21, 2022
Winning solution for the Galaxy Challenge on Kaggle

Winning solution for the Galaxy Challenge on Kaggle

Sander Dieleman 483 Jan 02, 2023
Iris species predictor app is used to classify iris species created using python's scikit-learn, fastapi, numpy and joblib packages.

Iris Species Predictor Iris species predictor app is used to classify iris species using their sepal length, sepal width, petal length and petal width

Siva Prakash 5 Apr 05, 2022
使用数学和计算机知识投机倒把

偷鸡不成项目集锦 坦率地讲,涉及金融市场的好策略如果公开,必然导致使用的人多,最后策略变差。所以这个仓库只收集我目前失败了的案例。 加密货币组合套利 中国体育彩票预测 我赚不上钱的项目,也许可以帮助更有能力的人去赚钱。

Roy 28 Dec 29, 2022
A high-performance topological machine learning toolbox in Python

giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G

giotto.ai 632 Dec 29, 2022
Gaussian Process Optimization using GPy

End of maintenance for GPyOpt Dear GPyOpt community! We would like to acknowledge the obvious. The core team of GPyOpt has moved on, and over the past

Sheffield Machine Learning Software 847 Dec 19, 2022
Simple linear model implementations from scratch.

Hand Crafted Models Simple linear model implementations from scratch. Table of contents Overview Project Structure Getting started Citing this project

Jonathan Sadighian 2 Sep 13, 2021
Bottleneck a collection of fast, NaN-aware NumPy array functions written in C.

Bottleneck Bottleneck is a collection of fast, NaN-aware NumPy array functions written in C. As one example, to check if a np.array has any NaNs using

Python for Data 835 Dec 27, 2022
flexible time-series processing & feature extraction

A corona statistics and information telegram bot.

PreDiCT.IDLab 206 Dec 28, 2022
A quick reference guide to the most commonly used patterns and functions in PySpark SQL

Using PySpark we can process data from Hadoop HDFS, AWS S3, and many file systems. PySpark also is used to process real-time data using Streaming and

Sundar Ramamurthy 53 Dec 21, 2022