Computational approaches leveraging integrated connections of multi-omic data toward clinical applications
In line with the advances in high-throughput technologies, multiple omic datasets have
accumulated to study biological systems and diseases coherently. No single omics data type …
accumulated to study biological systems and diseases coherently. No single omics data type …
scGWAS: landscape of trait-cell type associations by integrating single-cell transcriptomics-wide and genome-wide association studies
Background The rapid accumulation of single-cell RNA sequencing (scRNA-seq) data
presents unique opportunities to decode the genetically mediated cell-type specificity in …
presents unique opportunities to decode the genetically mediated cell-type specificity in …
Current and future directions in network biology
Network biology, an interdisciplinary field at the intersection of computational and biological
sciences, is critical for deepening understanding of cellular functioning and disease. While …
sciences, is critical for deepening understanding of cellular functioning and disease. While …
Identifying new cancer genes based on the integration of annotated gene sets via hypergraph neural networks
C Deng, HD Li, LS Zhang, Y Liu, Y Li, J Wang - Bioinformatics, 2024 - academic.oup.com
Motivation Identifying cancer genes remains a significant challenge in cancer genomics
research. Annotated gene sets encode functional associations among multiple genes, and …
research. Annotated gene sets encode functional associations among multiple genes, and …
DOMINO: a network‐based active module identification algorithm with reduced rate of false calls
Algorithms for active module identification (AMI) are central to analysis of omics data. Such
algorithms receive a gene network and nodes' activity scores as input and report …
algorithms receive a gene network and nodes' activity scores as input and report …
SuperDendrix algorithm integrates genetic dependencies and genomic alterations across pathways and cancer types
Recent genome-wide CRISPR-Cas9 loss-of-function screens have identified genetic
dependencies across many cancer cell lines. Associations between these dependencies …
dependencies across many cancer cell lines. Associations between these dependencies …
NetMix2: Unifying network propagation and altered subnetworks
A standard paradigm in computational biology is to use interaction networks to analyze high-
throughput biological data. Two common approaches for leveraging interaction networks …
throughput biological data. Two common approaches for leveraging interaction networks …
NetMix2: A Principled Network Propagation Algorithm for Identifying Altered Subnetworks
A standard paradigm in computational biology is to leverage interaction networks as prior
knowledge in analyzing high-throughput biological data, where the data give a score for …
knowledge in analyzing high-throughput biological data, where the data give a score for …
Calibrated nonparametric scan statistics for anomalous pattern detection in graphs
We propose a new approach, the calibrated nonparametric scan statistic (CNSS), for more
accurate detection of anomalous patterns in large-scale, real-world graphs. Scan statistics …
accurate detection of anomalous patterns in large-scale, real-world graphs. Scan statistics …
Quantifying and reducing bias in maximum likelihood estimation of structured anomalies
Anomaly estimation, or the problem of finding a subset of a dataset that differs from the rest
of the dataset, is a classic problem in machine learning and data mining. In both theoretical …
of the dataset, is a classic problem in machine learning and data mining. In both theoretical …