Chrom-Lasso: a lasso regression-based model to detect functional interactions using Hi-C data

J Lu, X Wang, K Sun, X Lan - Briefings in bioinformatics, 2021 - academic.oup.com
Hi-C is a genome-wide assay based on Chromosome Conformation Capture and high-
throughput sequencing to decipher 3D chromatin organization in the nucleus. However …

Mixture analysis using non‐negative elastic net for Raman spectroscopy

HT Zeng, MH Hou, YP Ni, Z Fang, XQ Fan… - Journal of …, 2020 - Wiley Online Library
Raman spectrum is wealth of structural information, which can be used as molecular
fingerprint to identify compounds. There are relations between the intensities of Raman …

Penalized and constrained LAD estimation in fixed and high dimension

X Wu, R Liang, H Yang - Statistical Papers, 2022 - Springer
Recently, many literatures have proved that prior information and structure in many
application fields can be formulated as constraints on regression coefficients. Following …

Penalized negative binomial models for modeling an overdispersed count outcome with a high-dimensional predictor space: Application predicting micronuclei …

RR Lehman, KJ Archer - PloS one, 2019 - journals.plos.org
Chromosomal aberrations, such as micronuclei (MN), have served as biomarkers of
genotoxic exposure and cancer risk. Guidelines for the process of scoring MN have been …

ROBOUT: a conditional outlier detection methodology for high-dimensional data

M Farnè, A Vouldis - Statistical Papers, 2024 - Springer
This paper presents a methodology, called ROBOUT, to identify outliers conditional on a
high-dimensional noisy information set. In particular, ROBOUT is able to identify …

An effective graph clustering method to identify cancer driver modules

W Zhang, Y Zeng, L Wang, Y Liu… - … in Bioengineering and …, 2020 - frontiersin.org
Identifying the molecular modules that drive cancer progression can greatly deepen the
understanding of cancer mechanisms and provide useful information for targeted therapies …

High-dimensional sign-constrained feature selection and grou**

S Qin, H Ding, Y Wu, F Liu - Annals of the Institute of Statistical …, 2021 - Springer
In this paper, we propose a non-negative feature selection/feature grou** (nnFSG)
method for general sign-constrained high-dimensional regression problems that allows …

Robust selection of predictors and conditional outlier detection in a perturbed large-dimensional regression context

M Farnè, A Vouldis - arxiv preprint arxiv:2104.12208, 2021 - arxiv.org
This paper presents a fast methodology, called ROBOUT, to identify outliers in a response
variable conditional on a set of linearly related predictors, retrieved from a large granular …

[PDF][PDF] Statistical Methods for Complex and/or High Dimensional Data

S Qin - 2020 - yorkspace.library.yorku.ca
This dissertation focuses on the development and implementation of statistical methods for
high-dimensional and/or complex data, with an emphasis on $ p $, the number of …

[PDF][PDF] Leveraging Analytics to Predict Geomagnetic Storms Impact to Global Telecommunications

TK Larkin, DJ McManus - DATA ANALYTICS 2016, 2016 - core.ac.uk
Coronal mass ejections are colossal bursts of magnetic field and plasma from the Sun.
These eruptions can have disastrous effects on Earth's telecommunication systems and …