Model-based quantification of protein-protein interaction aberrations for exploring dysregulated signalling pathways through pathway maps and gene expression levels [0.03%]
基于模型的蛋白质相互作用异常定量探索通过路径图和基因表达水平调节失调的信号通路
Kenta Kevee Kisaï,Takashi Omori
Kenta Kevee Kisaï
Background: Protein-protein interactions (PPIs) are fundamental components of signal transduction, and identifying dysregulated pathways is essential for understanding disease mechanisms. Conventional methods use pathway ...
Research on multi-trait genome association study method based on Shannon information entropy [0.03%]
基于香农信息熵的多性状基因组关联分析方法研究
Wanping Lv,Yiyuan Wang,Jingyu Wang et al.
Wanping Lv et al.
Background: Genetic analysis of complex traits is crucial for elucidating disease mechanisms and biological inheritance processes. However, traditional Genome-wide Association Study (GWAS) for single trait often fail to c...
A multi-view feature fusion framework with interpretable graph convolution for predicting microbe-drug associations [0.03%]
一种基于可解释图卷积的多视图特征融合框架用于预测微生物-药物关联
Lisha Zhou
Lisha Zhou
Predicting associations between human microbes and drugs (MDA) is a critical step in drug development and precision medicine. Although various computational approaches have been proposed, many existing models still struggle to reveal the ke...
Georgios Aliatimis,Ruriko Yoshida,Burak Boyacı et al.
Georgios Aliatimis et al.
In phylogenomics, species-tree methods must contend with two major sources of noise; stochastic gene-tree variation under the multispecies coalescent model (MSC) and finite-sequence substitutional noise. Fast agglomerative methods such as G...
Bradley T Martin,Domenico R Monaco,Nadine Sharabi et al.
Bradley T Martin et al.
Background: Population genomic workflows frequently rely on fragmented command-line utilities, custom conversion scripts, and programming language-specific environments, complicating computational reproducibility and obsc...
SpaHNR: a spatial domain identification method via sparse attention-based hierarchical node representation and multi-view contrastive learning [0.03%]
基于稀疏注意的层次节点表示和多视图对比学习的空间域识别方法SPAHR
Wei Peng,Zhihao Ping,Wei Dai et al.
Wei Peng et al.
Background: Leveraging deep learning on spatial transcriptomics data enables the identification of distinct spatial domains within tissues, thereby clarifies the spatial organization of cells and their gene expression. Th...
OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry [0.03%]
开放式的成像质谱流式单细胞和空间蛋白质组分析平台OpenIMC
Dean Tessone,Mohamed Kamal,Valerie Hennes et al.
Dean Tessone et al.
Background: Imaging Mass Cytometry (IMC) enables highly multiplexed, spatially resolved single-cell proteomics, providing simultaneous measurement of dozens of protein markers while preserving tissue architecture. Despite...
NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data [0.03%]
NAP：一个使用纳米孔测序数据进行跨领域微生物组分析的开源工作流程
Luke B Jones,Stefan Bagby
Luke B Jones
Background: Nanopore sequencing offers a cost-effective and portable platform for microbiome analysis, but amplicon-based approaches remain limited by higher sequencing error rates and a lack of workflows tailored to mixe...
SurvGME: an R package for survival analysis with graphical and measurement error models [0.03%]
SurvGME：一个用于生存分析的R包，结合图形和测量误差模型
Li-Pang Chen,Grace Y Yi
Li-Pang Chen
Background: Analyzing time-to-event data, such as cancer patient survival time, is a central task in survival analysis. Numerous modeling methods and inference strategies have been developed for various application settin...
SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint [0.03%]
基于本体相似性的贝叶斯网络推断方法研究基因调控网络inferencing_gene_regulatory_network_using_gene_ontology_similarity-based_bayesian_network_method
Maryam Shahdoust,Rosa Aghdam,Mehdi Sadeghi
Maryam Shahdoust
Gene regulatory network (GRN) reconstruction is a fundamental challenge in computational biology, and is crucial for understanding gene interactions. In this study, we aim to incorporate Gene Ontology (GO) similarities into the construction...