Ignas Rumbavicius,Trine B Rounge,Torbjørn Rognes
Ignas Rumbavicius
Background: Shotgun metagenome sequencing data obtained from a host environment will usually be contaminated with sequences from the host organism. Host sequences should be removed before further analysis to avoid biases,...
Reference-based genome compression using the longest matched substrings with parallelization consideration [0.03%]
基于最长匹配子串的参考基因组压缩及其并行化考虑
Zhiwen Lu,Lu Guo,Jianhua Chen et al.
Zhiwen Lu et al.
Background: A large number of researchers have devoted to accelerating the speed of genome sequencing and reducing the cost of genome sequencing for decades, and they have made great strides in both areas, making it easie...
Mathias Cardner,Francesco Marass,Erika Gedvilaite et al.
Mathias Cardner et al.
Background: Liquid biopsy is a minimally-invasive method of sampling bodily fluids, capable of revealing evidence of cancer. The distribution of cell-free DNA (cfDNA) fragment lengths has been shown to differ between heal...
DGDTA: dynamic graph attention network for predicting drug-target binding affinity [0.03%]
基于动态图注意力网络的药物-靶点结合亲和力预测模型
Haixia Zhai,Hongli Hou,Junwei Luo et al.
Haixia Zhai et al.
Background: Obtaining accurate drug-target binding affinity (DTA) information is significant for drug discovery and drug repositioning. Although some methods have been proposed for predicting DTA, the features of proteins...
A robust approach to 3D neuron shape representation for quantification and classification [0.03%]
稳健的三维神经元形状表征方法用于量化与分类
Jiaxiang Jiang,Michael Goebel,Cezar Borba et al.
Jiaxiang Jiang et al.
We consider the problem of finding an accurate representation of neuron shapes, extracting sub-cellular features, and classifying neurons based on neuron shapes. In neuroscience research, the skeleton representation is often used as a compa...
A heterogeneous graph convolutional attention network method for classification of autism spectrum disorder [0.03%]
自闭症谱系障碍分类的异构图卷积注意力网络方法
Lizhen Shao,Cong Fu,Xunying Chen
Lizhen Shao
Background: Autism spectrum disorder (ASD) is a serious developmental disorder of the brain. Recently, various deep learning methods based on functional magnetic resonance imaging (fMRI) data have been developed for the c...
Automatic echocardiographic anomalies interpretation using a stacked residual-dense network model [0.03%]
基于堆叠残差密集网络模型的自动心超异常解读方法
Siti Nurmaini,Ade Iriani Sapitri,Bambang Tutuko et al.
Siti Nurmaini et al.
Echocardiographic interpretation during the prenatal or postnatal period is important for diagnosing cardiac septal abnormalities. However, manual interpretation can be time consuming and subject to human error. Automatic segmentation of ec...
Fuzzy optimization for identifying antiviral targets for treating SARS-CoV-2 infection in the heart [0.03%]
针对SARS-CoV-2感染引起的心脏病变的抗病毒治疗靶点的模糊优化识别方法
Sz-Wei Chu,Feng-Sheng Wang
Sz-Wei Chu
In this paper, a fuzzy hierarchical optimization framework is proposed for identifying potential antiviral targets for treating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the heart. The proposed framework comp...
Inferring circadian gene regulatory relationships from gene expression data with a hybrid framework [0.03%]
基于基因表达数据的昼夜节律调控关系的混合框架推理方法
Shuwen Hu,Yi Jing,Tao Li et al.
Shuwen Hu et al.
Background: The central biological clock governs numerous facets of mammalian physiology, including sleep, metabolism, and immune system regulation. Understanding gene regulatory relationships is crucial for unravelling t...
CrMP-Sol database: classification, bioinformatic analyses and comparison of cancer-related membrane proteins and their water-soluble variant designs [0.03%]
CrMP-Sol数据库：癌症相关膜蛋白及其水溶变体设计的分类、生物信息学分析及比较
Lina Ma,Sitao Zhang,Qi Liang et al.
Lina Ma et al.
Membrane proteins are critical mediators for tumor progression and present enormous therapeutic potentials. Although gene profiling can identify their cancer-specific signatures, systematic correlations between protein functions and tumor-r...