Coarse-Grained Modeling of Biomolecular Networks: A Practical Guide
A practical guide to coarse-grained modeling of biomolecular networks: bead mapping, interaction potentials, system equilibration, and validation against reference data.
ML-Biomat
Tutorials, research notes, and practical guides on ML and multiscale modeling for fiber-based biomaterials. Home of FiberNet, a Python toolkit for fiber network design and optimization.
Tutorials, research notes, and practical guides on ML and multiscale modeling for fiber-based biomaterials. Home of FiberNet, a Python toolkit for fiber network design and optimization.
🦮 ML for Science
🔬 Multiscale Methods
🦪 Fiber Biomaterials
English Articles
Mechanical Testing of Biomaterials: A Reproducible Protocol Guide
A practical protocol-focused guide to reproducible mechanical testing of biomaterials, from specimen hydration and instrument setup to data reduction and a reporting checklist.
Setting Up a Python Scientific Computing Environment
A comprehensive three-platform guide covering virtual environments, Conda and Mamba, JupyterLab, and VS Code integration for materials science and biology graduate students.
Common Regression Models in Machine Learning
A systematic guide to linear regression, Ridge, Lasso, polynomial regression, SVR, decision trees, random forests, and gradient boosting for scientific and engineering applications, with complete code examples.
The Nature of Deep Learning
A systematic introduction to deep learning: neurons, activation functions, backpropagation, regularization, and transfer learning, with practical guidance on when deep learning is the right tool in materials science.
NetworkX Fundamentals with Python
A hands-on introduction to NetworkX for Python: build graphs from real data, compute centrality and connectivity metrics, and visualize networks for materials and biology research.
ML Classification Models: A Practical Overview
A practical guide to major classification models in machine learning - logistic regression, decision trees, SVMs, and gradient boosting - covering intuition, tradeoffs, and reusable Python code.
Engineered Superstructures: Origami, Lattices, and Beyond
A comprehensive review of engineered superstructures: origami, honeycomb, auxetic, helical, and lattice designs in 2D and 3D, covering geometry, mechanisms, parameters, and design rules.
Hierarchical Superstructures in Biomaterials
A navigational guide to hierarchical superstructures in biomaterials: silk fibroin, collagen, bone, nacre, spider silk, and cellulose analyzed through their structure-mechanics relationships.
GROMACS MD Tutorial: Structure Prep to Trajectory Analysis
A complete hands-on tutorial for GROMACS molecular dynamics simulation, covering installation, system preparation, energy minimization, equilibration, production MD, and trajectory analysis (RMSD/RMSF/Rg/H-bonds) using lysozyme as a worked example.
Stress-Strain Curves: A Materials Science Primer
A beginner-friendly guide to interpreting stress-strain curves: elastic modulus, yield strength, ultimate strength, toughness, and how these concepts apply to soft biomaterials.
Silk Fibroin: From Molecular Structure to Mechanical Function
How silk fibroin's hierarchical structure—from amino acid sequence to beta-sheet crystallites—dictates its remarkable mechanical properties and guides biomaterials design.