Bioinformatika (Bioinformatis)

Bioinformatis

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Practical-Machine-Learning-and-Image-Processing

Source Code for 'Practical Machine Learning and Image Processing' by Himanshu Singh

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2021_QSARcovid

Небольшой проект с попыткой найти что-то нормальное среди молекул

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adversarial-learning-robustness

Contains materials for workshops pertaining to adversarial robustness in deep learning.

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code

Compilation of R and Python programming codes on the Data Professor YouTube channel.

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data

kumpulan data

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deeplearning-models

A collection of various deep learning architectures, models, and tips

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DEEPScreen

DEEPScreen: Virtual Screening with Deep Convolutional Neural Networks Using Compound Images

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DiffusionDrawer

Diffusion models for 2D rendering of compounds

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hignn

Code for "HiGNN: A Hierarchical Informative Graph Neural Network for Molecular Property Prediction Equipped with Feature-Wise Attention"

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image

leaf

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ml_model_deployment_example

A simple example to showcase machine learning model deployment with an API

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ML_QSAR

This repo holds all the codes on all the machine learning models and the fuzzy logic model that has been created to solve this problem regarding the QSAR dataset.

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molecule-solubility

Molecule water solubility prediction using DeepChem.

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pattern_classification

A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks

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QSAR-falcipain-inhibitor

Bioinformatics project using QSAR with machine learning approach to predict falcipain inhibitor as potential anti-malarial agent

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QSAR-Modeling

Supervised machine learning for Quantitative Structure-Activity Relationship modeling

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QSAR-Modelling

Developing a regression-based QSAR (quantitative structure-activity relationships) model to identify compounds that have 3-chymotrypsin-like protease (3CLpro) inhibitory activity.

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QSAR_PFAS

This model contains code and data for developing QSAR models in the SCENARIOS project

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QSARapp

The app performs the QSAR modelling for topoisomerase II inhibitors. It takes SMILE of compounds as an input and give predicted values (82.70% accurate) of their bioactivity with topoisomerase II.

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SolubilityPrediction

A web based application predicts water solubility of any given chemical compound known or unknown

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YaSAScore

Prediction of compound synthesis accessibility bashed on reaction knowledge graph

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