Machine Learning Methods for Prostate Cancer Prediction using Magnetic Resonance Imaging and Clinical Data
Prostate cancer is one of the most common cancers in males and is difficult to diagnose in its early stages. Traditional methods have …
CCPA: cloud-based, self-learning modules for consensus pathway analysis using GO, KEGG and Reactome
This manuscript describes the development of a resource module that is part of a learning platform named ‘NIGMS Sandbox for Cloud-based …
SSA: a novel method for Single-cell and Spatial transcriptomics Alignment
Single-cell RNA sequencing (scRNA-seq) provides expression profiles of individual cells but fails to preserve crucial spatial …
RCPA: An Open-Source R Package for Data Processing, Differential Analysis, Consensus Pathway Analysis, and Visualization
Abstract Identifying impacted pathways is important because it provides insights into the biology underlying conditions beyond the …
Novel Techniques for Single-cell RNA Sequencing Data Imputation and Clustering
Advances in single-cell technologies have shifted genomics research from the analysis of bulk tissues toward a comprehensive …
Wave reduction efficiency for three classes of breakwaters on the coastal Mekong Delta
This study presents a laboratory scale implementation of breakwaters and their ability to mitigate extreme wave erosion on the coast of …
scCAN: single-cell clustering using autoencoder and network fusion
Unsupervised clustering of single-cell RNA sequencing data (scRNA-seq) is important because it allows us to identify putative cell …
A novel method for single-cell data imputation using subspace regression
Recent advances in biochemistry and single-cell RNA sequencing (scRNA-seq) have allowed us to monitor the biological systems at the …
scIDS: Single-cell Imputation by combining Deep autoencoder neural networks and Subspace regression
Single-cell RNA-sequencing (scRNA-seq) has emerged as a powerful high throughput technique that enables the characterization of …
SMRT: Randomized Data Transformation for Cancer Subtyping and Big Data Analysis
Cancer is an umbrella term that includes a range of disorders, from those that are fast-growing and lethal to indolent lesions with low …
Single-Cell RNA Sequencing Data Imputation Using Deep Neural Network
Recent research in biology has shifted the focus toward single-cell data analysis. The new single-cell technologies have allowed us to …
Fast and precise single-cell data analysis using a hierarchical autoencoder
A primary challenge in single-cell RNA sequencing (scRNA-seq) studies comes from the massive amount of data and the excess noise level. …
Disease subtyping using community detection from consensus networks
Cancer is a complex disease including a range of disorders that are activated simultaneously by multiple biological processes on …
A comprehensive survey of regulatory network inference methods using single-cell RNA sequencing data
Gene regulatory network is a complicated set of interactions between genetic materials, which dictates how cells develop in living …
RIA: a novel Regression-based Imputation Approach for single-cell RNA sequencing
Advances in single-cell technologies have shifted genomics research from the analysis of bulk tissues toward a comprehensive …
Sentiment Classification for Hotel Booking Review Based on Sentence Dependency Structure and Sub-Opinion Analysis
This paper presents a supervised method to classify a document at the sub-sentence level. Traditionally, sentiment analysis often …
Vietnamese Online Hotel Reviews Classification Bases on Term Features Selection
This paper aims to present the improved techniques to classify the user’s feedbacks on hotel service qualities. The data were …
Vietnamese Online Hotel Reviews Classification Bases on Term Features Selection
We propose an improved technique to analyze sentiment for Viet-namese texts based on term feature selection approach. The sentiment …
