UmarZein

user:

Based on these objective statements:

General Objective The overarching goal of this project is to develop a comprehensive, efficient, and scalable data infrastructure tailored for the pharmaceutical industry. This system aims to leverage advanced technologies such as graph databases, distributed computing, and real-time data streaming to enhance drug discovery, optimize clinical processes, and support data-driven decision-making. The project also seeks to foster greater collaboration within the pharmaceutical ecosystem and improve data accessibility and analysis capabilities.

Specific Objective Data Integration and Management:

	#include <math.h>
	#include <stdio.h>
	#include <stdlib.h>
	#include <time.h>

	int bernoulli_sample(double p) {
	return ((double) rand() / RAND_MAX) < p ? 1 : 0;
	}

	const double SECOND_SCALE=1000000000;

	libraries:
	-torchdrug
	-deepchem

	*) pytorch lebih stabil dan reliable daripada tensorflow, biasanya

	*) ada 2 approach terhadap NN-based drug design: SMILES-based dan graph-based dimana molekulnya dimodelkan sebagai graph.

	BioAssays of GLP-1: https://pubchem.ncbi.nlm.nih.gov/gene/2740#section=BioAssays