dwMLCS: An Efficient MLCS Algorithm based on Dynamic and Weighted Directed Acyclic Graph [0.03%]
基于动态和加权有向无环图的高效MLCS算法
Changyong Yu,Dekuan Gao,Xu Guo et al.
Changyong Yu et al.
The problem of finding the longest common subsequence (MLCS) for multiple sequences is a computationally intensive and challenging problem that has significant applications in various fields such as text comparison, pattern recognition, and...
Dopcc: Detecting overlapping protein complexes via multi-metrics and co-core attachment method [0.03%]
基于多指标和核心互连的蛋白质复合物的重叠识别方法（DOPCC）
Wenkang Wang,Xiangmao Meng,Ju Xiang et al.
Wenkang Wang et al.
Identification of protein complex is an important issue in the field of system biology, which is crucial to understanding the cellular organization and inferring protein functions. Recently, many computational methods have been proposed to ...
Enhancing Generalizability in Biomedical Entity Recognition: Self-Attention PCA-CLS Model [0.03%]
增强生物医学实体识别的泛化能力：自注意力PCA-CLS模型
Rajesh Kumar Mundotiya,Juhi Priya,Divya Kuwarbi et al.
Rajesh Kumar Mundotiya et al.
One of the primary tasks in the early stages of data mining involves the identification of entities from biomedical corpora. Traditional approaches relying on robust feature engineering face challenges when learning from available (un-)anno...
Employing Machine Learning Techniques to Detect Protein Function: A Survey, Experimental, and Empirical Evaluations [0.03%]
基于机器学习的蛋白质功能预测：调查、实验与实证评估
Kamal Taha
Kamal Taha
This review article delves deeply into the various machine learning (ML) methods and algorithms employed in discerning protein functions. Each method discussed is assessed for its efficacy, limitations, potential improvements, and future pr...
MOTHER-DB: A Database for Sharing Nonhuman Ovarian Histology Images [0.03%]
母体数据库：一个用于分享非人类卵巢组织学图像的数据库
Suzanne W Dietrich,Wenli Ma,Yian Ding et al.
Suzanne W Dietrich et al.
The goal of the Multispecies Ovary Tissue Histology Electronic Repository (MOTHER) project is to establish a collection of nonhuman ovary histology images for multiple species as a resource for researchers and educators. An important compon...
Bi-SeqCNN: A Novel Light-weight Bi-directional CNN Architecture for Protein Function Prediction [0.03%]
轻量级双向卷积神经网络在蛋白质功能预测中的应用
Vikash Kumar,Akshay Deepak,Ashish Ranjan et al.
Vikash Kumar et al.
Deep learning approaches, such as convolution neural networks (CNNs) and deep recurrent neural networks (RNNs), have been the backbone for predicting protein function, with promising state-of-the-art (SOTA) results. RNNs with an in-built ab...
SCRN: Single-cell Gene Regulatory Network Identification in Alzheimer's Disease [0.03%]
阿尔茨海默病单细胞基因调控网络识别
Wentao Zhu,Zhiqiang Du,Ziang Xu et al.
Wentao Zhu et al.
Alzheimer's disease (AD) is the most common neurodegenerative disease, and it consumes considerable medical resources with increasing number of patients every year. Mounting evidence show that the regulatory disruptions altering the intrins...
Improved Fuzzy Cognitive Maps for Gene Regulatory Networks Inference based on time series data [0.03%]
基于时间序列数据的基因调控网络推理的改进模糊认知地图方法
Marzieh Emadi,Farsad Zamani Boroujeni,Jamshid Pirgazi
Marzieh Emadi
Microarray data provide lots of information regarding gene expression levels. Due to the large amount of such data, their analysis requires sufficient computational methods for identifying and analyzing gene regulation networks; however, re...
AnglesRefine: Refinement of 3D Protein Structures Using Transformer Based on Torsion Angles [0.03%]
基于扭转角的Transformer的蛋白质三维结构 refinement (AnglesRefine)
Lei Zhang,Junyong Zhu,Sheng Wang et al.
Lei Zhang et al.
The goal of protein structure refinement is to enhance the precision of predicted protein models, particularly at the residue level of the local structure. Existing refinement approaches primarily rely on physics, whereas molecular simulati...
Graph Convolutional Network with Self-supervised Learning for Brain Disease Classification [0.03%]
基于自监督学习的图卷积网络脑疾病分类方法
Guangyu Wang,Ying Chu,Qianqian Wang et al.
Guangyu Wang et al.
Brain functional network (BFN) analysis has become a popular method for identifying neurological diseases at their early stages and revealing sensitive biomarkers related to these diseases. Due to the fact that BFN is a graph with complex s...