Contains functions to estimate
L-moments and trimmed L-moments from the data. Also
contains functions to estimate the parameters of the normal
polynomial quantile mixture and the Cauchy polynomial quantile
mixture from L-moments and trimmed L-moments.

c(person("Juha", "Karvanen", email = "juha.karvanen@iki.fi", role = c("cre", "aut")),
person("Santeri", "Karppinen", email = "santeri.j.karppinen@jyu.fi", role = "aut"))
Juha Karvanen [cre, aut],
Santeri Karppinen [aut]

Long Non-Coding RNA Identification Based on Features of
Sequence, EIIP and Secondary Structure
Han Siyu [aut, cre],
Li Ying [aut],
Liang Yanchun [aut]
Cheng Ming, Fan Linrui, Guo Yuan, Li Yaolong
Functions for predicting sequences are mRNAs or long non-coding RNAs.
Default models are trained on human, mouse and wheat datasets by employing
SVM. Features are based on intrinsic composition of sequence, EIIP value
(electron-ion interaction pseudopotential) and secondary structure. The model
can also be built on users' own data.

LncRNA Identification and Analysis Using Heterologous Features
c(
person(family = "HAN", given = "Siyu", email = "hansy15@mails.jlu.edu.cn", role = c("aut", "cre")),
person(family = "LI", given = "Ying", email = "liying@jlu.edu.cn", role = "aut"),
person(family = "LIANG", given = "Yanchun", role = "aut"))
CHENG Ming, FAN Linrui, GUO Yuan, LI Yaolong, SUN
Ying, WANG Ruoyu
Long non-coding RNAs identification and analysis. Default models are trained with human, mouse and wheat datasets by employing SVM. Features are based on intrinsic composition of sequence, EIIP value (electron-ion interaction pseudopotential), and secondary structure. This package can also extract other classic features and build new classifiers. Reference: Han SY., Liang YC., Li Y., et al. (2018) <doi:10.1093/bib/bby065>.
Siyu HAN [aut, cre],
Ying LI [aut],
Yanchun LIANG [aut]

Predicting Modulator and Functional/Survival Analysis
Yongsheng Li,Zishan Wang,Juan Xu*,Xia Li*
Predict modulators regulating the ability of effectors to regulate their targets and produce
modulator-effector-target triplets followed by goterm functional enrichment and survival analysis.This
is mainly applied to long non-coding RNAs (lncRNAs) as candidate modulators regulating the ability of
transcription factors (TFs) to regulate their corresponding targets.