Using Constrained-INC for Large-Scale Gene Tree and Species Tree Estimation [0.03%]
使用受限INC进行大规模基因树和物种树的估计
Thien Le,Aaron Sy,Erin K Molloy et al.
Thien Le et al.
Incremental tree building (INC) is a new phylogeny estimation method that has been proven to be absolute fast converging under standard sequence evolution models. A variant of INC, called Constrained-INC, is designed for use in divide-and-c...
GPU Accelerated Drug Application on Signaling Pathways Containing Multiple Faults Using Boolean Networks [0.03%]
基于布尔网络的含多个故障信号转导路径的GPU加速药物作用分析
Tapan Chowdhury,Susanta Chakraborty,Argha Nandan
Tapan Chowdhury
Cell growth is governed by the flow of information from growth factors to transcription factors. This flow involves protein-protein interactions known as a signaling pathway, which triggers the cell division. The biological network in the p...
MISSIM: An Incremental Learning-Based Model With Applications to the Prediction of miRNA-Disease Association [0.03%]
MISSIM：一种用于预测miRNA-疾病关联的基于增量学习的模型
Kai Zheng,Zhu-Hong You,Lei Wang et al.
Kai Zheng et al.
In the past few years, the prediction models have shown remarkable performance in most biological correlation prediction tasks. These tasks traditionally use a fixed dataset, and the model, once trained, is deployed as is. These models ofte...
Correction to "A Reaction-Based Model of the State Space of Chemical Reaction Systems Enables Efficient Simulations" [0.03%]
对“基于反应的化学反应系统状态空间模型实现了高效的模拟”的修正答复
Paola Lecca,Angela Re
Paola Lecca
Integrative Biological Network Analysis to Identify Shared Genes in Metabolic Disorders [0.03%]
综合生物学网络分析以发现代谢紊乱中的共有基因
Samet Tenekeci,Zerrin Isik
Samet Tenekeci
Identification of common molecular mechanisms in interrelated diseases is essential for better prognoses and targeted therapies. However, complexity of metabolic pathways makes it difficult to discover common disease genes underlying metabo...
Boltzmann Machine Learning and Regularization Methods for Inferring Evolutionary Fields and Couplings From a Multiple Sequence Alignment [0.03%]
从多重序列排列中推理boltzmann机学习和正则化方法以及进化场和耦合的最佳方式
Sanzo Miyazawa
Sanzo Miyazawa
The inverse Potts problem to infer a Boltzmann distribution for homologous protein sequences from their single-site and pairwise amino acid frequencies recently attracts a great deal of attention in the studies of protein structure and evol...
EBST: An Evolutionary Multi-Objective Optimization Based Tool for Discovering Potential Biomarkers in Ovarian Cancer [0.03%]
基于进化多目标优化的卵巢癌潜在生物标志物发现工具EBST
Hanif Yaghoobi,Esmaeil Babaei,Bashdar Mahmud Hussen et al.
Hanif Yaghoobi et al.
Ovarian cancer is the deadliest gynecologic malignancy, mainly due to limitations in early diagnosis. With advances in high-throughput technologies, research interest in identifying novel and customized tumor biomarkers for early detection ...
Andre Rodrigues Oliveira,Geraldine Jean,Guillaume Fertin et al.
Andre Rodrigues Oliveira et al.
Genome rearrangements are mutations affecting large portions of a genome, and a reversal is one of the most studied genome rearrangements in the literature through the Sorting by Reversals (SbR) problem. SbR is solvable in polynomial time o...
Comparing Phylogenetic Approaches to Reconstructing Cell Lineage From Microsatellites With Missing Data [0.03%]
比较从微卫星构建细胞谱系的系统发生方法（具有缺失数据）
Anne-Marie Lyne,Leila Perie
Anne-Marie Lyne
Due to the imperfect fidelity of DNA replication, somatic cells acquire DNA mutations at each division which record their lineage history. Microsatellites, tandem repeats of DNA nucleotide motifs, mutate more frequently than other genomic r...
Unsupervised Learning Framework With Multidimensional Scaling in Predicting Epithelial-Mesenchymal Transitions [0.03%]
基于多维缩放的无监督学习框架在上皮间质转化预测中的应用
Yushan Qiu,Hao Jiang,Wai-Ki Ching
Yushan Qiu
Clustering tumor metastasis samples from gene expression data at the whole genome level remains an arduous challenge, in particular, when the number of experimental samples is small and the number of genes is huge. We focus on the predictio...