The required hardware, software skills, and knowledge to build a computation platform for drug discovery from scratch.
Sargol Mazraedoost
High-Performance Computing (HPC) Cluster: Invest in dedicated HPC resources for computational tasks. Powerful Workstations: Equip research workstations with high-performance CPUs and GPUs. Storage Infrastructure: Set up scalable and high-capacity storage for handling large datasets. Data Backup and Redundancy: Implement data backup and redundancy solutions for data protection. Molecular Modeling Software: Use software like Schrödinger Suite, AutoDock, GROMACS, and CHARMM. Chemoinformatics Tools: Employ tools for compound library management and virtual screening. Bioinformatics Software: Analyze genomics data and identify drug targets using bioinformatics tools. Machine Learning and Data Science: Utilize Python, R, TensorFlow, and PyTorch for predictive modeling. Database Management: Manage databases for chemical and biological data. Data Visualization: Visualize research findings with tools like Matplotlib and Tableau. Version Control: Use Git for code versioning and repository management. Linux/Unix Skills: Navigate Linux/Unix for data management and simulations. Scripting and Programming: Automate tasks with Python and other scripting languages. Parallel Computing: Harness the power of multi-core processors and HPC clusters. Pharmaceutical and Biochemical Knowledge: Understand pharmacology and medicinal chemistry for drug target identification. Bioinformatics and Chemoinformatics: Analyze data and perform structure-activity relationship (SAR) studies. Molecular Biology: Grasp DNA, RNA, and protein structure and function. Machine Learning and Data Science: Apply ML and data science for predictive modeling. Regulatory and Ethical Considerations: Stay compliant with regulatory guidelines and ethical standards.
Hardware Requirements:
Software and Skills:
Knowledge and Expertise:
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Hammed Hammidat
This requires programming skills and software knowledge to build a computational website
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Andrew Sutton
Define your new medicine discovery pathways first. Design the software/hardware second. The first is the more difficult. How do you beat the big Pfizer-scale beasts already in the field?
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