Chrom-Lasso: a lasso regression-based model to detect functional interactions using Hi-C data
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 …
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 …
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 …
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 …
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 …
high-dimensional noisy information set. In particular, ROBOUT is able to identify …
An effective graph clustering method to identify cancer driver modules
Identifying the molecular modules that drive cancer progression can greatly deepen the
understanding of cancer mechanisms and provide useful information for targeted therapies …
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 …
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 …
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 …
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 …
These eruptions can have disastrous effects on Earth's telecommunication systems and …