An Integrative Framework of Heterogeneous Genomic Data for Cancer Dynamic Modules Based on Matrix Decomposition [0.03%]
基于矩阵分解的癌症动态模块的异源基因组数据整合框架
Xiaoke Ma,Penggang Sun,Maoguo Gong
Xiaoke Ma
Cancer progression is dynamic, and tracking dynamic modules is promising for cancer diagnosis and therapy. Accumulated genomic data provide us an opportunity to investigate the underlying mechanisms of cancers. However, as far as we know, n...
Yan Liu,Hao Liang,Quan Zou et al.
Yan Liu et al.
The identification of essential proteins is an important problem in bioinformatics. During the past decades, many centrality measures and algorithms have been proposed to address this issue. However, existing methods still deserve the follo...
Evaluation of Experimental Protocols for Shotgun Whole-Genome Metagenomic Discovery of Antibiotic Resistance Genes [0.03%]
霰弹枪全基因组宏基因组发现抗生素抗性基因的实验方案评估
Ken Hung-On Yu,Xiunan Fang,Haobin Yao et al.
Ken Hung-On Yu et al.
Shotgun metagenomics has enabled the discovery of antibiotic resistance genes (ARGs). Although there have been numerous studies benchmarking the bioinformatics methods for shotgun metagenomic data analysis, there has not yet been a study th...
A Scalable Embedding Based Neural Network Method for Discovering Knowledge From Biomedical Literature [0.03%]
一种可扩展的嵌入式神经网络方法从生物医学文献中发现知识
Shengtian Sang,Xiaoxia Liu,Xiaoyu Chen et al.
Shengtian Sang et al.
Nowadays, the amount of biomedical literatures is growing at an explosive speed, and much useful knowledge is yet undiscovered in the literature. Classical information retrieval techniques allow to access explicit information from a given c...
protein2vec: Predicting Protein-Protein Interactions Based on LSTM [0.03%]
protein2vec：基于LSTM预测蛋白质-蛋白质相互作用
Jiongmin Zhang,Man Zhu,Ying Qian
Jiongmin Zhang
The semantic similarity of gene ontology (GO) terms is widely used to predict protein-protein interactions (PPIs). The traditional semantic similarity measures are based mainly on manually crafted features, which may ignore some important h...
GuiltyTargets: Prioritization of Novel Therapeutic Targets With Network Representation Learning [0.03%]
有罪目标：用网络表示学习对新型治疗目标进行优先级排序
Ozlem Muslu,Charles Tapley Hoyt,Mauricio Lacerda et al.
Ozlem Muslu et al.
The majority of clinical trials fail due to low efficacy of investigated drugs, often resulting from a poor choice of target protein. Existing computational approaches aim to support target selection either via genetic evidence or by puttin...
CIR-Net: Automatic Classification of Human Chromosome Based on Inception-ResNet Architecture [0.03%]
基于Inception-ResNet架构的自动人类染色体分类研究
Chengchuang Lin,Gansen Zhao,Zhirong Yang et al.
Chengchuang Lin et al.
Background: In medicine, karyotyping chromosomes is important for medical diagnostics, drug development, and biomedical research. Unfortunately, chromosome karyotyping is usually done by skilled cytologists manually, whic...
An Efficient Multiresolution Clustering for Motif Discovery in Complex Networks [0.03%]
复杂网络中基于多分辨率聚类的高效模体发现方法
Mahdi Pursalim,Kwoh Chee Keong
Mahdi Pursalim
Motif discovery and network clustering in complex networks have received a lot of attention in recent years, also they are still challenging tasks in bioinformatics, big data analytics and data mining applications. Motif discovery in big da...
Yu-Ting Tan,Le Ou-Yang,Xingpeng Jiang et al.
Yu-Ting Tan et al.
It is an important task to learn how gene regulatory networks change under different conditions. Several Gaussian graphical model-based methods have been proposed to deal with this task by inferring differential networks from gene expressio...
On Monomeric and Multimeric Structures-Based Protein-Ligand Interactions [0.03%]
基于单体和多聚体结构的蛋白-配体相互作用研究
Yajun Dai,Yang Li,Liping Wang et al.
Yajun Dai et al.
Many ligands simultaneously interact with multiple protein chains in quaternary structure (QS). However, a significant number of previous studies on template-based modeling of protein-ligand interactions were based on monomeric structure (M...