regnet.pkl

In this work, we build a knowledge-based database, named RegNetwork , of gene regulatory networks for human and mouse by collecting and integrating the documented regulatory interactions among transcription factors (TFs), microRNAs (miRNAs) and target genes from 25 selected databases. Moreover, we also inferred and incorporated potential regulatory relationships based on transcription factor binding site (TFBS) motifs into RegNetwork. As a result, RegNetwork contains a comprehensive set of experimentally observed or predicted transcriptional and post-transcriptional regulatory relationships, and the database framework is flexibly designed for potential extensions to include gene regulatory networks for other organisms in the future.

在本研究中，我们构建了一个基于知识的数据库，命名为RegNetwork，其中包含了人类和小鼠的基因调控网络。该数据库通过收集并整合来自25个精选数据库中记录的转录因子（TFs）、微小RNA（miRNAs）与靶基因之间的调控相互作用而构建。此外，我们还在RegNetwork中推断并纳入了基于转录因子结合位点（TFBS）基序的潜在调控关系。因此，RegNetwork包含了实验观察或预测的转录和后转录调控关系的全面集合，且数据库框架设计灵活，便于未来扩展以纳入其他生物体的基因调控网络。