A Deep Learning Model for RNA-Protein Binding Preference Prediction Based on Hierarchical LSTM and Attention Network [0.03%]
基于层次LSTM和注意力网络的RNA-蛋白结合偏好预测模型
Zhen Shen,Qinhu Zhang,Kyungsook Han et al.
Zhen Shen et al.
Attention mechanism has the ability to find important information in the sequence. The regions of the RNA sequence that can bind to proteins are more important than those that cannot bind to proteins. Neither conventional methods nor deep l...
Optimal Robust Search for Parameter Values of Qualitative Models of Gene Regulatory Networks [0.03%]
基因调控网络定性模型参数值的最优鲁棒搜索
Liliana Ironi,Ettore Lanzarone
Liliana Ironi
Computational and mathematical models are a must for the in silico analysis or design of Gene Regulatory Networks (GRN)as they offer a theoretical context to deeply address biological regulation. We have proposed a framework where models of...
A Hierarchical Discriminative Sparse Representation Classifier for EEG Signal Detection [0.03%]
用于EEG信号检测的分级判别稀疏表示分类器
Xiaoqing Gu,Cong Zhang,Tongguang Ni
Xiaoqing Gu
Classification of electroencephalogram (EEG) signal data plays a vital role in epilepsy detection. Recently sparse representation-based classification (SRC) methods have achieved the good performance in EEG signal automatic detection, by wh...
SSKM_Succ: A Novel Succinylation Sites Prediction Method Incorporating K-Means Clustering With a New Semi-Supervised Learning Algorithm [0.03%]
SSKM_Succ：结合K-均值聚类与新的半监督学习算法的新型琥珀酰化位点预测方法
Qiao Ning,Zhiqiang Ma,Xiaowei Zhao et al.
Qiao Ning et al.
Protein succinylation is a type of post-translational modification (PTM) that occurs on lysine sites and plays a key role in protein conformation regulation and cellular function control. When training in computational method, it is difficu...
Predicting Local Protein 3D Structures Using Clustering Deep Recurrent Neural Network [0.03%]
使用聚类深度循环神经网络预测局部蛋白质三维结构
Wei Zhong,Feng Gu
Wei Zhong
Since protein 3D structure prediction is very important for biochemical study and drug design, researchers have developed many machine learning algorithms to predict protein 3D structures using the sequence information only. Understanding t...
An Improved Topology Prediction of Alpha-Helical Transmembrane Protein Based on Deep Multi-Scale Convolutional Neural Network [0.03%]
基于深度多尺度卷积神经网络的α-螺旋跨膜蛋白拓扑预测改进研究
Yuning Yang,Jiawen Yu,Zhe Liu et al.
Yuning Yang et al.
Alpha-helical proteins ( αTMPs) are essential in various biological processes. Despite their tertiary structures are crucial for revealing complex functions, experimental structure determination remains challenging and costly. In the past ...
DCHap: A Divide-and-Conquer Haplotype Phasing Algorithm for Third-Generation Sequences [0.03%]
DCHap:一种处理第三代序列的单体型阻塞的分治算法
Yanbo Li,Yu Lin
Yanbo Li
The development of DNA sequencing technologies makes it possible to obtain reads originated from both copies of a chromosome (two parental chromosomes, or haplotypes) of a single individual. Reconstruction of both haplotypes (i.e., haplotyp...
Analysis of Pattern Formation by Colored Petri Nets With Quantitative Regulation of Gene Expression Level [0.03%]
基于定量基因表达调控的有色彩Petri网图案形成分析方法研究
Fei Liu,Ena Yamamoto,Katsunobu Shirahama et al.
Fei Liu et al.
Modeling and simulation are becoming indispensable tools for studying multicellular events such as pattern formation during embryonic development. In this paper, we propose a new approach for analyzing multicellular biological phenomena by ...
Network Classification Based on Reducibility With Respect to the Stability of Canalizing Power of Genes in a Gene Regulatory Network - A Boolean Network Modeling Perspective [0.03%]
基于基因调控网络中基因控权稳定性的可约简性网络分类——布尔网络建模视角
Eunji Kim,Ivan Ivanov,Edward R Dougherty
Eunji Kim
A key objective of studying biological systems is to design therapeutic intervention strategies for beneficially altering cell dynamics. Derivation of control policies is hindered by the high-dimensional state spaces associated with gene re...
JUPPI: A Multi-Level Feature Based Method for PPI Prediction and a Refined Strategy for Performance Assessment [0.03%]
JUPPI：用于PPI预测的多级特征方法和性能评估的改进策略
Anup Kumar Halder,Soumyendu Sekhar Bandyopadhyay,Piyali Chatterjee et al.
Anup Kumar Halder et al.
Over the years, several methods have been proposed for the computational PPI prediction with different performance evaluation strategies. While attempting to benchmark performance scores, most of these methods often suffer with ill-treated ...