Integrating node embeddings and biological annotations for genes to predict disease-gene associations [0.03%]
结合节点嵌入和生物标志以预测疾病基因关联
Sezin Kircali Ata,Le Ou-Yang,Yuan Fang et al.
Sezin Kircali Ata et al.
Background: Predicting disease causative genes (or simply, disease genes) has played critical roles in understanding the genetic basis of human diseases and further providing disease treatment guidelines. While various co...
Analysis of significant protein abundance from multiple reaction-monitoring data [0.03%]
基于多重反应监测数据的显著性蛋白质丰度分析
Jongsu Jun,Jungsoo Gim,Yongkang Kim et al.
Jongsu Jun et al.
Background: Discovering reliable protein biomarkers is one of the most important issues in biomedical research. The ELISA is a traditional technique for accurate quantitation of well-known proteins. Recently, the multiple...
A unified solution for different scenarios of predicting drug-target interactions via triple matrix factorization [0.03%]
一种基于三重矩阵分解的药物-靶点相互作用预测通用解法
Jian-Yu Shi,An-Qi Zhang,Shao-Wu Zhang et al.
Jian-Yu Shi et al.
Background: During the identification of potential candidates, computational prediction of drug-target interactions (DTIs) is important to subsequent expensive validation in wet-lab. DTI screening considers four scenarios...
Optimizing gene set annotations combining GO structure and gene expression data [0.03%]
综合利用GO结构和基因表达数据优化基因集合注释
Dong Wang,Jie Li,Rui Liu et al.
Dong Wang et al.
Background: With the rapid accumulation of genomic data, it has become a challenge issue to annotate and interpret these data. As a representative, Gene set enrichment analysis has been widely used to interpret large mole...
Hot spot prediction in protein-protein interactions by an ensemble system [0.03%]
基于集成系统的蛋白质-蛋白质相互作用热点预测方法研究
Quanya Liu,Peng Chen,Bing Wang et al.
Quanya Liu et al.
Background: Hot spot residues are functional sites in protein interaction interfaces. The identification of hot spot residues is time-consuming and laborious using experimental methods. In order to address the issue, many...
FMSM: a novel computational model for predicting potential miRNA biomarkers for various human diseases [0.03%]
FMSM：一种新颖的计算模型 用于预测各种人类疾病的潜在miRNA生物标志物
Yiwen Sun,Zexuan Zhu,Zhu-Hong You et al.
Yiwen Sun et al.
Background: MicroRNA (miRNA) plays a key role in regulation mechanism of human biological processes, including the development of disease and disorder. It is necessary to identify potential miRNA biomarkers for various hu...
Laplacian normalization and bi-random walks on heterogeneous networks for predicting lncRNA-disease associations [0.03%]
拉普拉斯标准化和双随机游走算法在异构网络上用于预测长链非编码核糖核酸-疾病关联
Yaping Wen,Guosheng Han,Vo V Anh
Yaping Wen
Background: Evidences have increasingly indicated that lncRNAs (long non-coding RNAs) are deeply involved in important biological regulation processes leading to various human complex diseases. Experimental investigations...
Multi-CSAR: a multiple reference-based contig scaffolder using algebraic rearrangements [0.03%]
基于代数排列的多参考染色体支架算法（Multi-CSAR）
Kun-Tze Chen,Hsin-Ting Shen,Chin Lung Lu
Kun-Tze Chen
Background: One of the important steps in the process of assembling a genome sequence from short reads is scaffolding, in which the contigs in a draft genome are ordered and oriented into scaffolds. Currently, several sca...
rPCMP: robust p-value combination by multiple partitions with applications to ATAC-seq data [0.03%]
稳健的分区p值组合方法及其在ATAC测序数据中的应用
Menglan Cai,Limin Li
Menglan Cai
Background: Evaluating the significance for a group of genes or proteins in a pathway or biological process for a disease could help researchers understand the mechanism of the disease. For example, identifying related pa...
Network-based logistic regression integration method for biomarker identification [0.03%]
基于网络的逻辑回归整合方法用于生物标志物识别
Ke Zhang,Wei Geng,Shuqin Zhang
Ke Zhang
Background: Many mathematical and statistical models and algorithms have been proposed to do biomarker identification in recent years. However, the biomarkers inferred from different datasets suffer a lack of reproducibil...