Title: Integrated Tool for Hairping Extraction of RNA Sequences
Description: Simple and integrated tool that automatically extracts and folds all hairpin sequences from raw genome-wide data. It predicts the secondary structure of several overlapped segments, with longer length than the mean length of sequences of interest for the species under processing, ensuring that no one is lost nor inappropriately cut.
Imports: seqinr, parallel, doParallel, foreach,

Title: Hierarchical Heterogeneity Analysis via Penalization
c(person("Mingyang", "Ren", email = "renmingyang17@mails.ucas.ac.cn", role = c("aut", "cre"),
person("Qingzhao", "Zhang", role = c("aut")),
person("Sanguo", "Zhang", role = c("aut")),
person("Tingyan", "Zhong", role = c("aut")),
person("Jian", "Huang", role = c("aut")),
person("Shuangge", "Ma", role = c("aut")))
Description: In medical research, supervised heterogeneity analysis has important implications. Assume that there are two types of features. Using both types of features, our goal is to conduct the first supervised heterogeneity analysis that satisfies a hierarchical structure. That is, the first type of features defines a rough structure, and the second type defines a nested and more refined structure. A penalization approach is developed, which has been motivated by but differs significantly from penalized fusion and sparse group penalization.
Ren, M., Zhang, Q., Zhang, S., Zhong, T., Huang, J. & Ma, S. (2022). "Hierarchical cancer heterogeneity analysis based on histopathological imaging features". Biometrics, <doi:10.1111/biom.13426>.
Author: Mingyang Ren [aut, cre] (<https://orcid.org/0000-0002-8061-9940>),

Title: Systematic Analysis of Architectural Proteins and Functional
Elements in Blocking Long-Range Contacts Between Loci
Imports: IRanges, GenomeInfoDb, methods, GenomicRanges, Matrix, glmnet,
Description: Here we propose a model to systematically analyze the roles of architectural proteins and functional elements in blocking long-range contacts between loci. The proposed model does not rely on topologically associating domain (TAD) mapping from Hi-C data. Instead of testing the enrichment or influence of protein binding at TAD borders, the model directly estimates the blocking effect of proteins on long-range contacts between flanking loci, making the model intuitive and biologically meaningful.