Data for "Inferring protein folding mechanisms from natural sequence diversity"
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Description This repository contains the data associated with the article:"Inferring protein folding mechanisms from natural sequence diversity"Authors: Ezequiel A. Galpern, Ernesto A. Roman, Diego U. FerreiroDOI: 10.1016/j.bpj.2025.06.034 The dataset includes: Multiple Sequence Alignments (MSAs): Provided as .fasta files for 15 protein families. Potts Models: Saved as Python dictionaries in .npz format, which include: h: Local fields of the Potts model. J: Couplings of the Potts model. This dataset is designed to support reproducibility and further exploration of the findings presented in the article. Data Structure /simplified_rbm_and_msa/: Contains a folder for each of the 15 protein families. Each folder includes: A .fasta file for the multiple sequence alignment (MSA) of the protein family. A .npz file containing the Potts model, with local fields (h) and couplings (J), saved in NumPy format. File Format Details MSA Files Format: .fasta Example Usage: Load using any standard MSA tool or Python libraries such as Biopython. Potts Model Files Format: .npz (NumPy compressed archive) Contents: h: Local fields, accessible as potts['h']. J: Couplings, accessible as potts['J']. Example Usage: import numpy as np potts = np.load("potts_file.npz") h = potts['h'] # Local fields J = potts['J'] # Couplings Usage Instructions To use this dataset, refer to the corresponding GitHub repository, which includes: Codebase: All scripts required to process and analyze the data. Demonstration Notebook: A ready-to-run Jupyter Notebook for Google Colab. GitHub Repository Access the repository here: github.com/eagalpern/folding-ising-globular Citing This Dataset If you use this dataset, please cite: Galpern, E. A., Roman, E. A., & Ferreiro, D. U. (2025). "Inferring protein folding mechanisms from natural sequence diversity". Biophysical Journal . DOI: 10.1016/j.bpj.2025.06.034 .
# 数据集说明 本仓库包含与论文《基于天然序列多样性推断蛋白质折叠机制》（Inferring protein folding mechanisms from natural sequence diversity）相关的数据集。作者：埃泽基尔·A·加珀恩（Ezequiel A. Galpern）、埃内斯托·A·罗曼（Ernesto A. Roman）、迭戈·U·费雷罗（Diego U. Ferreiro）。DOI：10.1016/j.bpj.2025.06.034 本数据集包含： 1. 多序列比对（Multiple Sequence Alignments, MSAs）：为15个蛋白质家族提供了.fasta格式的比对文件。 2. Potts模型（Potts Models）：以Python字典格式保存于.npz压缩文件中，包含以下内容： - 局部场（Local fields）h - 耦合项（Couplings）J 本数据集旨在支持本文研究发现的可复现性及后续探索。 ## 数据结构 /simplified_rbm_and_msa/ 目录下为15个蛋白质家族各建立了一个子文件夹，每个子文件夹包含： - 对应蛋白质家族多序列比对的.fasta格式文件 - 以NumPy格式保存的、包含局部场h与耦合项J的Potts模型.npz文件 ## 文件格式细节 ### 多序列比对文件 - 格式：.fasta - 使用示例：可通过任意标准多序列比对工具或Python库（如Biopython）加载。 ### Potts模型文件 - 格式：.npz（NumPy压缩归档文件） - 内容： - `h`：局部场，可通过`potts['h']`访问 - `J`：耦合项，可通过`potts['J']`访问 - 使用示例： python import numpy as np potts = np.load("potts_file.npz") h = potts['h'] # 局部场 J = potts['J'] # 耦合项 ## 使用说明 使用本数据集请参考对应的GitHub仓库，其中包含： - 代码库：用于处理与分析本数据集的全部脚本 - 演示笔记：适用于Google Colab的可直接运行Jupyter Notebook ### GitHub仓库 可通过以下链接访问仓库：github.com/eagalpern/folding-ising-globular ## 引用说明 若使用本数据集，请引用以下文献： Galpern, E. A., Roman, E. A., & Ferreiro, D. U. (2025). "Inferring protein folding mechanisms from natural sequence diversity". Biophysical Journal . DOI: 10.1016/j.bpj.2025.06.034 .
