Abdul Karim

Smiles2vec. Proof of the concept implementation of smiles2vec paper

CardioTox. Python

Chemception. CNN model based on Google Inception model to predict regression values of regression values of Tetrahymena pyriformis IGC50 from 2D images of molcules

HybridTox2D. In recent times, toxicological classification of chemical compounds is considered to be a grand challenge for pharma-ceutical and environment regulators. Advancement in machine learning techniques enabled efficient toxicity predic-tion pipelines. Random forests (RF), support vector machines (SVM) and deep neural networks (DNN) are often ap-plied to model the toxic effects of chemical compounds. However, complexity-accuracy tradeoff still needs to be ac-counted in order to improve the efficiency and commercial deployment of these methods. In this study, we implement a hybrid framework consists of a shallow neural network and a decision classifier for toxicity prediction of chemicals that interrupt nuclear receptor (NR) and stress response (SR) signaling pathways. A model based on proposed hybrid framework is trained on Tox21 data using 2D chemical descriptors that are less multifarious in nature and easy to calcu-late. Our method achieved the highest accuracy of 0.847 AUC (area under the curve) using a shallow neural network with only one hidden layer consisted of 10 neurons. Furthermore, our hybrid model enabled us to elucidate the inter-pretation of most important descriptors responsible for NR and SR toxicity.

50_layer_Resnet. 50 Layer Resnet to predict the regression values of Tetrahymena pyriformis IGC50 from 2d molecular images only

HPE. Heterogeneous Predictors Ensembling for Quantitative Toxicity Prediction

QuantitativeTox. Python

New_molecules_generation. Character level RNN to generate new molecules

Name-Entity-Recognition. Recognize named entities on Twitter with LSTMs

Intro-to-probability-and-data-project. Exploratory data analysis for Behavioral Risk Factor Surveillance System (BRFSS) dataset

ALALI. Automated Loading assuming Atomic Level Interactions (ALALI): A python tool to map atoms to qubits, including IBM Q topologies. GPL-3.0-or-later.

Tag_Prediction_Multiclassification. Multi-classifier for Stack-overflow tag prediction using logistic regression

Intent_classification. My demo code and a report for Intent classification

Leander_colab. Next_Project