Articles

Polymorphisms in the mTOR-PI3K-Akt pathway, energy balance-related exposures and colorectal cancer risk in the Netherlands Cohort Study

The mTOR-PI3K-Akt pathway influences cell metabolism and (malignant) cell growth. We generated sex-specific polygenic risk scores capturing natural variation in 7 out of 10 top-ranked genes in this pathway. We...

Authors: Colinda C.J.M. Simons, Leo J. Schouten, Roger W.L. Godschalk, Frederik-Jan van Schooten, Monika Stoll, Kristel Van Steen, Piet A. van den Brandt and Matty P. Weijenberg

Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data

Single-cell RNA sequencing (scRNA-seq) data provide valuable insights into cellular heterogeneity which is significantly improving the current knowledge on biology and human disease. One of the main applicatio...

Authors: Pelin Gundogdu, Carlos Loucera, Inmaculada Alamo-Alvarez, Joaquin Dopazo and Isabel Nepomuceno

Machine learning approaches for the genomic prediction of rheumatoid arthritis and systemic lupus erythematosus

Rheumatoid arthritis (RA) and systemic lupus erythematous (SLE) are autoimmune rheumatic diseases that share a complex genetic background and common clinical features. This study’s purpose was to construct mac...

Authors: Chih-Wei Chung, Tzu-Hung Hsiao, Chih-Jen Huang, Yen-Ju Chen, Hsin-Hua Chen, Ching-Heng Lin, Seng-Cho Chou, Tzer-Shyong Chen, Yu-Fang Chung, Hwai-I Yang and Yi-Ming Chen

Identification of natural selection in genomic data with deep convolutional neural network

With the increase in the size of genomic datasets describing variability in populations, extracting relevant information becomes increasingly useful as well as complex. Recently, computational methodologies su...

Authors: Arnaud Nguembang Fadja, Fabrizio Riguzzi, Giorgio Bertorelle and Emiliano Trucchi

LPI-EnEDT: an ensemble framework with extra tree and decision tree classifiers for imbalanced lncRNA-protein interaction data classification

Long noncoding RNAs (lncRNAs) have dense linkages with various biological processes. Identifying interacting lncRNA-protein pairs contributes to understand the functions and mechanisms of lncRNAs. Wet experime...

Authors: Lihong Peng, Ruya Yuan, Ling Shen, Pengfei Gao and Liqian Zhou

Gaussian noise up-sampling is better suited than SMOTE and ADASYN for clinical decision making

Clinical data sets have very special properties and suffer from many caveats in machine learning. They typically show a high-class imbalance, have a small number of samples and a large number of parameters, an...

Authors: Jacqueline Beinecke and Dominik Heider

Development of glaucoma predictive model and risk factors assessment based on supervised models

To develop and to propose a machine learning model for predicting glaucoma and identifying its risk factors.

Authors: Mahyar Sharifi, Toktam Khatibi, Mohammad Hassan Emamian, Somayeh Sadat, Hassan Hashemi and Akbar Fotouhi

Correction to: iGlioSub: an integrative transcriptomic and epigenomic classifier for glioblastoma molecular subtypes

Authors: Miquel Ensenyat-Mendez, Sandra Íñiguez-Muñoz, Borja Sesé and Diego M. Marzese

Prediction of synergistic drug combinations using PCA-initialized deep learning

Cancer is one of the main causes of death worldwide. Combination drug therapy has been a mainstay of cancer treatment for decades and has been shown to reduce host toxicity and prevent the development of acqui...

Authors: Jun Ma and Alison Motsinger-Reif

Humans and machines in biomedical knowledge curation: hypertrophic cardiomyopathy molecular mechanisms’ representation

Biomedical knowledge is dispersed in scientific literature and is growing constantly. Curation is the extraction of knowledge from unstructured data into a computable form and could be done manually or automat...

Authors: Mila Glavaški and Lazar Velicki

Evaluation of different approaches for missing data imputation on features associated to genomic data

Missing data is a common issue in different fields, such as electronics, image processing, medical records and genomics. They can limit or even bias the posterior analysis. The data collection process can lead...

Authors: Ben Omega Petrazzini, Hugo Naya, Fernando Lopez-Bello, Gustavo Vazquez and Lucía Spangenberg

Taxonomy-based data representation for data mining: an example of the magnitude of risk associated with H. pylori infection

The amount of available and potentially significant data describing study subjects is ever growing with the introduction and integration of different registries and data banks. The single specific attribute of...

Authors: Inese Polaka, Danute Razuka-Ebela, Jin Young Park and Marcis Leja

iGlioSub: an integrative transcriptomic and epigenomic classifier for glioblastoma molecular subtypes

Glioblastoma (GBM) is the most aggressive and prevalent primary brain tumor, with a median survival of 15 months. Advancements in multi-omics profiling combined with computational algorithms have unraveled the...

Authors: Miquel Ensenyat-Mendez, Sandra Íñiguez-Muñoz, Borja Sesé and Diego M. Marzese

Comparison of 16S and whole genome dog microbiomes using machine learning

Recent advances in sequencing technologies have driven studies identifying the microbiome as a key regulator of overall health and disease in the host. Both 16S amplicon and whole genome shotgun sequencing tec...

Authors: Scott Lewis, Andrea Nash, Qinghong Li and Tae-Hyuk Ahn

Development and validation of a novel blending machine learning model for hospital mortality prediction in ICU patients with Sepsis

Early prediction of hospital mortality is crucial for ICU patients with sepsis. This study aimed to develop a novel blending machine learning (ML) model for hospital mortality prediction in ICU patients with s...

Authors: Zhixuan Zeng, Shuo Yao, Jianfei Zheng and Xun Gong

Prediction of MoRFs based on sequence properties and convolutional neural networks

Intrinsically disordered proteins possess flexible 3-D structures, which makes them play an important role in a variety of biological functions. Molecular recognition features (MoRFs) act as an important type ...

Authors: Hao He, Yatong Zhou, Yue Chi and Jingfei He

Probability calibration-based prediction of recurrence rate in patients with diffuse large B-cell lymphoma

Although many patients receive good prognoses with standard therapy, 30–50% of diffuse large B-cell lymphoma (DLBCL) cases may relapse after treatment. Statistical or computational intelligent models are power...

Authors: Shuanglong Fan, Zhiqiang Zhao, Yanbo Zhang, Hongmei Yu, Chuchu Zheng, Xueqian Huang, Zhenhuan Yang, Meng Xing, Qing Lu and Yanhong Luo

Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient

The last decade has seen a major increase in the availability of genomic data. This includes expert-curated databases that describe the biological activity of genes, as well as high-throughput assays that meas...

Authors: Haripriya Harikumar, Thomas P. Quinn, Santu Rana, Sunil Gupta and Svetha Venkatesh

GenoVault: a cloud based genomics repository

GenoVault is a cloud-based repository for handling Next Generation Sequencing (NGS) data. It is developed using OpenStack-based private cloud with various services like keystone for authentication, cinder for ...

Authors: Sankalp Jain, Amit Saxena, Suprit Hesarur, Kirti Bhadhadhara, Neeraj Bharti, Sunitha Manjari Kasibhatla, Uddhavesh Sonavane and Rajendra Joshi

Biological knowledge-slanted random forest approach for the classification of calcified aortic valve stenosis

Calcific aortic valve stenosis (CAVS) is a fatal disease and there is no pharmacological treatment to prevent the progression of CAVS. This study aims to identify genes potentially implicated with CAVS in pati...

Authors: Erika Cantor, Rodrigo Salas, Harvey Rosas and Sandra Guauque-Olarte

Evaluating risk detection methods to uncover ontogenic-mediated adverse drug effect mechanisms in children

Identifying adverse drugs effects (ADEs) in children, overall and within pediatric age groups, is essential for preventing disability and death from marketed drugs. At the same time, however, detection is chal...

Authors: Nicholas P. Giangreco and Nicholas P. Tatonetti

Machine-learning based feature selection for a non-invasive breathing change detection

Chronic Obstructive Pulmonary Disease (COPD) is one of the top 10 causes of death worldwide, representing a major public health problem. Researchers have been looking for new technologies and methods for patie...

Authors: Juliana Alves Pegoraro, Sophie Lavault, Nicolas Wattiez, Thomas Similowski, Jésus Gonzalez-Bermejo and Etienne Birmelé

eQTpLot: a user-friendly R package for the visualization of colocalization between eQTL and GWAS signals

Genomic studies increasingly integrate expression quantitative trait loci (eQTL) information into their analysis pipelines, but few tools exist for the visualization of colocalization between eQTL and GWAS res...

Authors: Theodore G. Drivas, Anastasia Lucas and Marylyn D. Ritchie

A new pipeline for structural characterization and classification of RNA-Seq microbiome data

High-throughput sequencing enables the analysis of the composition of numerous biological systems, such as microbial communities. The identification of dependencies within these systems requires the analysis a...

Authors: Sebastian Racedo, Ivan Portnoy, Jorge I. Vélez, Homero San-Juan-Vergara, Marco Sanjuan and Eduardo Zurek

New neural network classification method for individuals ancestry prediction from SNPs data

Artificial Neural Network (ANN) algorithms have been widely used to analyse genomic data. Single Nucleotide Polymorphisms(SNPs) represent the genetic variations, the most common in the human genome, it has been s...

Authors: H. Soumare, S. Rezgui, N. Gmati and A. Benkahla

A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC su...

Authors: Qian Yan, Wenjiang Zheng, Boqing Wang, Baoqian Ye, Huiyan Luo, Xinqian Yang, Ping Zhang and Xiongwen Wang

A maximum flow-based network approach for identification of stable noncoding biomarkers associated with the multigenic neurological condition, autism

Machine learning approaches for predicting disease risk from high-dimensional whole genome sequence (WGS) data often result in unstable models that can be difficult to interpret, limiting the identification of...

Authors: Maya Varma, Kelley M. Paskov, Brianna S. Chrisman, Min Woo Sun, Jae-Yoon Jung, Nate T. Stockham, Peter Y. Washington and Dennis P. Wall

Estimating sequencing error rates using families

As next-generation sequencing technologies make their way into the clinic, knowledge of their error rates is essential if they are to be used to guide patient care. However, sequencing platforms and variant-ca...

Authors: Kelley Paskov, Jae-Yoon Jung, Brianna Chrisman, Nate T. Stockham, Peter Washington, Maya Varma, Min Woo Sun and Dennis P. Wall

Machine learning and statistical approaches for classification of risk of coronary artery disease using plasma cytokines

As per the 2017 WHO fact sheet, Coronary Artery Disease (CAD) is the primary cause of death in the world, and accounts for 31% of total fatalities. The unprecedented 17.6 million deaths caused by CAD in 2016 u...

Authors: Seema Singh Saharan, Pankaj Nagar, Kate Townsend Creasy, Eveline O. Stock, James Feng, Mary J. Malloy and John P. Kane

Coupling sparse Cox models with clustering of longitudinal transcriptomics data for trauma prognosis

Longitudinal gene expression analysis and survival modeling have been proved to add valuable biological and clinical knowledge. This study proposes a novel framework to discover gene signatures and patterns in...

Authors: Cláudia S. Constantino, Alexandra M. Carvalho and Susana Vinga

Prescreening and treatment of aortic dissection through an analysis of infinite-dimension data

Aortic dissection (AD) is one of the most catastrophic aortic diseases associated with a high mortality rate. In contrast to the advances in most cardiovascular diseases, both the incidence and in-hospital mor...

Authors: Peng Qiu, Yixuan Li, Kai Liu, Jinbao Qin, Kaichuang Ye, Tao Chen and Xinwu Lu

Prediction of short-term mortality in acute heart failure patients using minimal electronic health record data

Acute heart failure (AHF) is associated with significant morbidity and mortality. Effective patient risk stratification is essential to guiding hospitalization decisions and the clinical management of AHF. Cli...

Authors: Ashwath Radhachandran, Anurag Garikipati, Nicole S. Zelin, Emily Pellegrini, Sina Ghandian, Jacob Calvert, Jana Hoffman, Qingqing Mao and Ritankar Das

Ten important roles for academic leaders to promote equity, diversity, and inclusion in data science

Authors: Jason H. Moore, Van Q. Truong, Ashley B. Robbins, David Nicholson and Clar Lynda Williams-Devane

A multi-feature hybrid classification data mining technique for human-emotion

The ideal treatment of illnesses is the interest of every era. Data innovation in medical care has become extremely quick to analyze diverse diseases from the most recent twenty years. In such a finding, past ...

Authors: Y. Wang, Y. M. Chu, A. Thaljaoui, Y. A. Khan, W. Chammam and S. Z. Abbas

Indels in SARS-CoV-2 occur at template-switching hotspots

The evolutionary dynamics of SARS-CoV-2 have been carefully monitored since the COVID-19 pandemic began in December 2019. However, analysis has focused primarily on single nucleotide polymorphisms and largely ...

Authors: Brianna Sierra Chrisman, Kelley Paskov, Nate. Stockham, Kevin Tabatabaei, Jae-Yoon Jung, Peter Washington, Maya Varma, Min Woo Sun, Sepideh Maleki and Dennis P. Wall

RASMA: a reverse search algorithm for mining maximal frequent subgraphs

Given a collection of coexpression networks over a set of genes, identifying subnetworks that appear frequently is an important research problem known as mining frequent subgraphs. Maximal frequent subgraphs a...

Authors: Saeed Salem, Mohammed Alokshiya and Mohammad Al Hasan

Genetic risk score for ovarian cancer based on chromosomal-scale length variation

Twin studies indicate that a substantial fraction of ovarian cancers should be predictable from genetic testing. Genetic risk scores can stratify women into different classes of risk. Higher risk women can be ...

Authors: Christopher Toh and James P. Brody

A comparative study on the unified model based multifactor dimensionality reduction methods for identifying gene-gene interactions associated with the survival phenotype

For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely employed to reduce multi-levels of gene-gene interactions into high- or low-risk groups using a binary ...

Authors: Jung Wun Lee and Seungyeoun Lee

Performance of model-based multifactor dimensionality reduction methods for epistasis detection by controlling population structure

In genome-wide association studies the extent and impact of confounding due to population structure have been well recognized. Inadequate handling of such confounding is likely to lead to spurious associations...

Authors: Fentaw Abegaz, François Van Lishout, Jestinah M. Mahachie John, Kridsadakorn Chiachoompu, Archana Bhardwaj, Diane Duroux, Elena S. Gusareva, Zhi Wei, Hakon Hakonarson and Kristel Van Steen

DASSI: differential architecture search for splice identification from DNA sequences

The data explosion caused by unprecedented advancements in the field of genomics is constantly challenging the conventional methods used in the interpretation of the human genome. The demand for robust algorit...

Authors: Shabir Moosa, Prof. Abbes Amira and Dr. Sabri Boughorbel

Gene function finding through cross-organism ensemble learning

Structured biological information about genes and proteins is a valuable resource to improve discovery and understanding of complex biological processes via machine learning algorithms. Gene Ontology (GO) cont...

Authors: Gianluca Moro and Marco Masseroli

The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation

Evaluating binary classifications is a pivotal task in statistics and machine learning, because it can influence decisions in multiple areas, including for example prognosis or therapies of patients in critica...

Authors: Davide Chicco, Niklas Tötsch and Giuseppe Jurman

Data analytics and clinical feature ranking of medical records of patients with sepsis

Sepsis is a life-threatening clinical condition that happens when the patient’s body has an excessive reaction to an infection, and should be treated in one hour. Due to the urgency of sepsis, doctors and phys...

Authors: Davide Chicco and Luca Oneto

Acoustic and language analysis of speech for suicidal ideation among US veterans

Screening for suicidal ideation in high-risk groups such as U.S. veterans is crucial for early detection and suicide prevention. Currently, screening is based on clinical interviews or self-report measures. Bo...

Authors: Anas Belouali, Samir Gupta, Vaibhav Sourirajan, Jiawei Yu, Nathaniel Allen, Adil Alaoui, Mary Ann Dutton and Matthew J. Reinhard

Sparse self-attention aggregation networks for neural sequence slice interpolation

Microscopic imaging is a crucial technology for visualizing neural and tissue structures. Large-area defects inevitably occur during the imaging process of electron microscope (EM) serial slices, which lead to...

Authors: Zejin Wang, Jing Liu, Xi Chen, Guoqing Li and Hua Han

A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactions

Non-additive interactions among genes are frequently associated with a number of phenotypes, including known complex diseases such as Alzheimer’s, diabetes, and cardiovascular disease. Detecting interactions r...

Authors: Alena Orlenko and Jason H. Moore

Empowering the data science scientist

Authors: Jason H. Moore

Feature selection using distributions of orthogonal PLS regression vectors in spectral data

Feature selection, which is important for successful analysis of chemometric data, aims to produce parsimonious and predictive models. Partial least squares (PLS) regression is one of the main methods in chemo...

Authors: Geonseok Lee and Kichun Lee

Privacy-preserving chi-squared test of independence for small samples

The importance of privacy protection in analyses of personal data, such as genome-wide association studies (GWAS), has grown in recent years. GWAS focuses on identifying single-nucleotide polymorphisms (SNPs) ...

Authors: Yuichi Sei and Akihiko Ohsuga

Mechanistic modeling of the SARS-CoV-2 disease map

Here we present a web interface that implements a comprehensive mechanistic model of the SARS-CoV-2 disease map. In this framework, the detailed activity of the human signaling circuits related to the viral in...

Authors: Kinza Rian, Marina Esteban-Medina, Marta R. Hidalgo, Cankut Çubuk, Matias M. Falco, Carlos Loucera, Devrim Gunyel, Marek Ostaszewski, María Peña-Chilet and Joaquín Dopazo