河南工业大学 生物工程学院 & 信息科学与工程学院 · 生物工程（主修） & 计算机科学与技术（辅修） | 大二在读
我现在是大二学生，主修生物工程，同时辅修计算机。平时主要花时间在计算生物学上，尤其是酶工程的理性设计、分子动力学模拟和高性能计算这几个方向。一个人慢慢攒了一套自己的工作流：从序列分析、突变预测，到搭建自动化模拟管线，再到用 C++ 和 CUDA 写一些底层工具，算是把整个链条都摸了一遍。这些过程我都写成了博客，代码也开源在社区里，希望能帮到同样在这个坑里的人。
I'm currently a sophomore majoring in Biological Engineering with a minor in Computer Science. My main focus is computational biology – specifically rational enzyme design, molecular dynamics simulations, and GPU-accelerated computing. I've built a personal toolchain covering everything from sequence analysis and mutation prediction to automated simulation pipelines and low-level C++/CUDA libraries. I document the journey on my blog and share code openly; hopefully it's useful to others tinkering in the same space.
主要课程：生物化学、分子生物学、基因工程、细胞生物学；Python/C++ 程序设计、数据结构、算法基础、数据库原理、Linux 系统使用。
Henan University of Technology (expected 2028) – Major: Biological Engineering, Minor: Computer Science. GPA 3.6/4.0. Core courses include Biochemistry, Molecular Biology, Genetic Engineering, Python/C++ Programming, Data Structures, Algorithms, and Linux.
| 酶工程与蛋白设计 | FoldX、DynaMut2、CataPro、DLKcat、多序列比对、保守性分析、关键氨基酸识别、突变体设计 |
|---|---|
| 分子模拟与药物发现 | AutoDock Vina、PLIP、GROMACS（多体系）、RMSD/RMSF/Rg/DCCM/MM‑PBSA 分析、虚拟筛选流程 |
| 计算生物学软件开发 | C++ (STL, 性能优化)、CUDA 并行编程、蛋白质文件解析 (PDB/mmCIF)、特征计算引擎、Rosetta Python 包 |
| 计算化学与ML方法 | ORCA、MultiWFN（RESP 电荷计算）、FlexTrimmer（机器学习驱动的蛋白柔性特征预测）、ResNet残差神经网络探索 |
| 其他工具 | Git、Linux Shell、Python (Flask/NumPy)、HTML/CSS/JavaScript、数据库基础、自动化部署与文档撰写 |
Built an automated pipeline that strings together sequence retrieval, MSA, conservation analysis, pocket identification, and mutation screening. Integrated FoldX, DynaMut2, CataPro/DLKcat to go from sequence to rational mutation suggestions, complete with ΔΔG heatmaps and activity reports.
Developed a full pipeline from pocket detection → Vina docking → PLIP interaction analysis for large-scale virtual screening. Wrote standardized GROMACS scripts covering four common system types, and bundled a post-analysis toolkit (RMSD, RMSF, Rg, DCCM, MM‑PBSA, etc.). Also authored a theoretical tutorial on MD from statistical mechanics, published on my docs site and GitHub.
A high‑performance, extensible C++ library for reading PDB and mmCIF files. Supports chain/residue/atom hierarchy and serves as the foundation for downstream geometric tools like pocket center calculation and feature engine.
C++ engine for pocket center, residue depth, SASA, and other structural descriptors. BioCUDA is a planned GPU‑accelerated library for molecular simulations and docking (including a Vina‑CUDA port). Also built a Rosetta Python wrapper for automated docking and analysis.
Built a batch RESP charge derivation workflow using ORCA and MultiWFN for MD parameterization. Developed FlexTrimmer, an ML-based tool for predicting optimal protein truncation sites to improve expression. Future work includes exploring ResNet models (e.g., ESM) for Protein function parameter prediction .
从生物问题到算法实现，再到工具开发和底层加速，我慢慢形成了一套自己的纵向能力栈。一个人把酶工程应用、分子模拟管线、高性能计算工具都摸了一遍，现在更想在蛋白质科学、计算药物发现或者高性能生物计算这些方向继续深入学习，也希望能找到志同道合的人一起做点有意思的事情。
I've gradually built a vertical stack spanning from biological questions down to algorithms, tools, and GPU acceleration. Having touched enzyme engineering applications, MD simulation pipelines, and high‑performance computing libraries, I'm now eager to dive deeper into protein science, computational drug discovery, or high‑performance biocomputing, and to collaborate with others who share these interests.