AAindex-PPII: Predicting polyproline type II helix structure based on amino acid indexes with an improved BiGRU-TextCNN model [0.03%]
基于改进的BiGRU-TextCNN模型利用氨基酸指数预测多脯氨酸II型螺旋结构
Jiasheng He,Shun Zhang,Chun Fang
Jiasheng He
The polyproline-II (PPII) structure domain is crucial in organisms' signal transduction, transcription, cell metabolism, and immune response. It is also a critical structural domain for specific vital disease-associated proteins. Recognizin...
iAMY-RECMFF: Identifying amyloidgenic peptides by using residue pairwise energy content matrix and features fusion algorithm [0.03%]
基于残基能量含量矩阵和特征融合算法的肽类淀粉样蛋白判定(iAMY-RECMFF)
Zizheng Yu,Zhijian Yin,Hongliang Zou
Zizheng Yu
Various diseases, including Huntington's disease, Alzheimer's disease, and Parkinson's disease, have been reported to be linked to amyloid. Therefore, it is crucial to distinguish amyloid from non-amyloid proteins or peptides. While experim...
CBDT-Oglyc: Prediction of O-glycosylation sites using ChiMIC-based balanced decision table and feature selection [0.03%]
基于ChiMIC的平衡决策表和特征选择预测O-糖基化位点(CBDT-Oglyc)
Ying Zeng,Zheming Yuan,Yuan Chen et al.
Ying Zeng et al.
O-glycosylation (Oglyc) plays an important role in various biological processes. The key to understanding the mechanisms of Oglyc is identifying the corresponding glycosylation sites. Two critical steps, feature selection and classifier des...
Analyzing omics data by feature combinations based on kernel functions [0.03%]
基于核函数的特征组合的组学数据分析方法研究
Chao Li,Tianxiang Wang,Xiaohui Lin
Chao Li
Defining meaningful feature (molecule) combinations can enhance the study of disease diagnosis and prognosis. However, feature combinations are complex and various in biosystems, and the existing methods examine the feature cooperation in a...
Methods for cell-type annotation on scRNA-seq data: A recent overview [0.03%]
单细胞RNA测序数据的细胞类型注释方法最新研究进展
Konstantinos Lazaros,Panagiotis Vlamos,Aristidis G Vrahatis
Konstantinos Lazaros
The evolution of single-cell technology is ongoing, continually generating massive amounts of data that reveal many mysteries surrounding intricate diseases. However, their drawbacks continue to constrain us. Among these, annotating cell ty...
A model-based clustering algorithm with covariates adjustment and its application to lung cancer stratification [0.03%]
基于模型的并含协变量调整的聚类算法及其在肺癌分层中的应用
Carlos E M Relvas,Asuka Nakata,Guoan Chen et al.
Carlos E M Relvas et al.
Usually, the clustering process is the first step in several data analyses. Clustering allows identify patterns we did not note before and helps raise new hypotheses. However, one challenge when analyzing empirical data is the presence of c...
Multi-omics data analysis reveals the biological implications of alternative splicing events in lung adenocarcinoma [0.03%]
多组学数据综合分析揭示肺腺癌可变剪接事件的生物学意义
Fuyan Hu,Bifeng Chen,Qing Wang et al.
Fuyan Hu et al.
Cancer is characterized by the dysregulation of alternative splicing (AS). However, the comprehensive regulatory mechanisms of AS in lung adenocarcinoma (LUAD) are poorly understood. Here, we displayed the AS landscape in LUAD based on the ...
Facilitating the drug repurposing with iC/E strategy: A practice on novel nNOS inhibitor discovery [0.03%]
利用iC/E策略促进老药新用：一项新型nNOS抑制剂发现实践研究
Zhaoyang Hu,Qingsen Liu,Zhong Ni
Zhaoyang Hu
Over the past decades, many existing drugs and clinical/preclinical compounds have been repositioned as new therapeutic indication from which they were originally intended and to treat off-target diseases by targeting their noncognate prote...
DeepRT: Predicting compounds presence in pathway modules and classifying into module classes using deep neural networks based on molecular properties [0.03%]
基于分子特性的深度神经网络预测化合物在途径模块中的存在情况及其所属模块类型
Hayat Ali Shah,Juan Liu,Zhihui Yang et al.
Hayat Ali Shah et al.
Metabolic pathways play a crucial role in understanding the biochemistry of organisms. In metabolic pathways, modules refer to clusters of interconnected reactions or sub-networks representing specific functional units or biological process...
Maria Waldl,Thomas Spicher,Ronny Lorenz et al.
Maria Waldl et al.
Most of the functional RNA elements located within large transcripts are local. Local folding therefore serves a practically useful approximation to global structure prediction. Due to the sensitivity of RNA secondary structure prediction t...