Data-Driven Boolean Network Inference Using a Genetic Algorithm With Marker-Based Encoding [0.03%]
基于标记的编码遗传算法的数据驱动布尔网络推理方法研究
Xiang Liu,Ning Shi,Yan Wang et al.
Xiang Liu et al.
The inference of Boolean networks is crucial for analyzing the topology and dynamics of gene regulatory networks. Many data-driven approaches using evolutionary algorithms have been proposed based on time-series data. However, the ability t...
Joao Schapke,Anderson Tavares,Mariana Recamonde-Mendoza
Joao Schapke
Identifying essential genes and proteins is a critical step towards a better understanding of human biology and pathology. Computational approaches helped to mitigate experimental constraints by exploring machine learning (ML) methods and t...
Design-for-Trust Techniques for Digital Microfluidic Biochip Layout with Error Control Mechanism [0.03%]
具备错误控制机制的数字微流控生物芯片布局的可信设计技术
Debasis Gountia,Sudip Roy
Debasis Gountia
Among recent technological advances, microfluidic biochips have been leading a prominent solution for healthcare and miniaturized bio-laboratories with the assurance of high sensitivity and reconfigurability. On increasing more unreliable c...
Detection of Tandem Repeats in DNA Sequences Using Short-Time Ramanujan Fourier Transform [0.03%]
基于短时拉曼juan变换的DNA序列串联重复检测方法研究
Yashpal Yadav,Sanjeev Narayan Sharma,Devendra Kumar Shakya
Yashpal Yadav
Tandem repeats in genomic sequences are characterized by two or more contiguous copies of a pattern of nucleotides. The role of these repeats as molecular markers is well established in various genetic disorders, human evolution studies, DN...
CEPZ: A Novel Predictor for Identification of DNase I Hypersensitive Sites [0.03%]
CEPZ：一种用于识别DNase I超敏感位点的新型预测器
Yan Zheng,Hao Wang,Yijie Ding et al.
Yan Zheng et al.
DNase I hypersensitive sites (DHSs) have proven to be tightly associated with cis-regulatory elements, commonly indicating specific function on the chromatin structure. Thus, identifying DHSs plays a fundamental role in decoding gene regula...
iEnhancer-KL: A Novel Two-Layer Predictor for Identifying Enhancers by Position Specific of Nucleotide Composition [0.03%]
基于核苷酸组成的位点特异性新型两层预测器(iEnhancer-KL)识别增强子
Yinuo Lyu,Zhen Zhang,Jiawei Li et al.
Yinuo Lyu et al.
An enhancer is a short region of DNA with the ability to recruit transcription factors and their complexes, increasing the likelihood of the transcription of a particular gene. Considering the importance of enhancers, enhancer identificatio...
The Determination of Distinctive Single Nucleotide Polymorphism Sets for the Diagnosis of Behçet's Disease [0.03%]
用于Behçet病诊断的特征性单核苷酸多态集合的确立
Yunus Emre Isik,Yasin Gormez,Zafer Aydin et al.
Yunus Emre Isik et al.
Behçet's Disease (BD) is a multi-system inflammatory disorder in which the etiology remains unclear. The most probable hypothesis is that genetic tendency and environmental factors play roles in the development of BD. In order to find the ...
An Ensemble Hybrid Feature Selection Method for Neuropsychiatric Disorder Classification [0.03%]
一种用于神经精神疾病分类的混合特征选择方法
Liangliang Liu,Shaojie Tang,Fang-Xiang Wu et al.
Liangliang Liu et al.
Magnetic resonance imagings (MRIs) are providing increased access to neuropsychiatric disorders that can be made available for advanced data analysis. However, the single type of data limits the ability of psychiatrists to distinguish the s...
Classification of Mild Cognitive Impairment With Multimodal Data Using Both Labeled and Unlabeled Samples [0.03%]
基于标注及非标注样本的多模态轻度认知障碍分类研究
Shaoxun Yuan,Haitao Li,Jiansheng Wu et al.
Shaoxun Yuan et al.
Mild Cognitive Impairment (MCI) is a preclinical stage of Alzheimer's Disease (AD) and is clinical heterogeneity. The classification of MCI is crucial for the early diagnosis and treatment of AD. In this study, we investigated the potential...
EEG-Based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications [0.03%]
基于脑电的脑机接口(BCI)研究：信号采集技术和计算智能方法及其应用综述
Xiaotong Gu,Zehong Cao,Alireza Jolfaei et al.
Xiaotong Gu et al.
Brain-Computer interfaces (BCIs) enhance the capability of human brain activities to interact with the environment. Recent advancements in technology and machine learning algorithms have increased interest in electroencephalographic (EEG)-b...