Prediction of chromatin looping using deep hybrid learning(DHL)

作     者：Mateusz Chilinski Anup Kumar Halder Dariusz Plewczynski Mateusz Chiliński;Anup Kumar Halder;Dariusz Plewczynski

作者机构：Faculty of Mathematics and Information SciencesWarsaw University of Technology00-662 WarsawPoland Laboratory of Functional and Structural Genomics Centre of New Technologies University of Warsaw02-097 WarsawPoland 

出 版 物：《Quantitative Biology》 (定量生物学（英文版）)

年 卷 期：2023年第11卷第2期

页      面：155-162页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Science Centre,Poland(Nos.2019/35/O/ST6/02484 and 2020/37/B/NZ2/03757) Foundation for Polish Science,co-financed by the European Union under the European Regional Development Fund(TEAM to DP) The work has been co-supported by European Commission Horizon 2020 Marie Skodowska-Curie ITN Enhpathy grant“Molecular Basis of Human enhanceropathies”and National Institute of Health USA 4DNucleome grant 1U54DK107967-01“Nucleome Positioning System for Spatiotemporal Genome Organization and Regulation”:Research was co-funded by Warsaw University of Technology within the Excellence Initiative:Research University(IDUB)programme.Computations were performed thanks to the Laboratory of Bioinformatics and Computational Genomics,Faculty of Mathematics and Information Science,Warsaw University of Technology using the Artificial Intelligence HPC platform financed by Polish Ministry of Science and Higher Education(No.7054/IA/SP/2020 of 2020-08-28) 

主　　题：deep learning 3D genomics transformers spatial organisation of nucleus ChIA-PET DNA-Seq 

摘      要：Background:With the development of rapid and cheap sequencing techniques,the cost of whole-genome sequencing(WGS)has dropped ***,the complexity of the human genome is not limited to the pure sequenceand additional experiments are required to learn the human genome s influence on complex *** of the most exciting aspects for scientists nowadays is the spatial organisation of the genome,which can be discovered using spatial experiments(e.g.,Hi-C,ChIA-PET).The information about the spatial contacts helps in the analysis and brings new insights into our understanding of the disease ***:We have used an ensemble of deep learning with classical machine learning *** deep learning network we used was DNABERT,which utilises the BERT language model(based on transformers)for the genomic *** classical machine learning models included support vector machines(SVMs),random forests(RFs),and K-nearest neighbor(KNN).The whole approach was wrapped together as deep hybrid learning(DHL).Results:We found that the DNABERT can be used to predict the ChIA-PET experiments with high ***,the DHL approach has increased the metrics on CTCF and RNAPII ***:DHL approach should be taken into consideration for the models utilising the power of deep *** straightforward in the concept,it can improve the results significantly.