Boinformatics-2018-10-1-目录

1.基因分析

 --Using standard microbiome reference groups to simplify beta-diversity analyses and facilitate independent validation 

使用标准微生物组参考组来简化β多样性分析并促进独立验证

 --Grouper: graph-based clustering and annotation for improved de novo transcriptome analysis 

   Grouper:基于图形的聚类和注释,用于改进从头转录组分析

--Modeling one thousand intron length distributions with fitild 

使用fitild建模一千个内含子长度分布

2.序列分析

--In silico read normalization using set multi-cover optimization

使用集合多覆盖优化的计算机读取规范化

--PBRpredict-Suite: a suite of models to predict peptide-recognition domain residues from protein sequence 

   PBRpredict-Suite:一套预测蛋白质序列中肽识别结构域残基的模型

--LZW-Kernel: fast kernel utilizing variable length code blocks from LZW compressors for protein sequence classification

LZW-Kernel:利用LZW压缩机的可变长度代码块进行蛋白质序列分类的快速内核

3.结构生物信息学

--GapRepairer: a server to model a structural gap and validate it using topological analysis 

  GapRepairer:用于建模结构间隙并使用拓扑分析对其进行验证的服务器

--High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features

使用完全卷积神经网络和最小序列特征进行蛋白质接触预测的高精度

--Applying graph theory to protein structures: an Atlas of coiled coils 

将图论应用于蛋白质结构:卷曲螺旋图谱

--MICAN-SQ: a sequential protein structure alignment program that is applicable to monomers and all types of oligomers 

MICAN-SQ:顺序蛋白质结构比对程序,适用于单体和所有类型的低聚物

4.基因表达

--RWEN: response-weighted elastic net for prediction of chemosensitivity of cancer cell lines 

RWEN:响应加权弹性网,用于预测癌细胞系的化学敏感性

--Two-phase differential expression analysis for single cell RNA-seq

  单细胞RNA-seq的两阶段差异表达分析

 --Bayesian negative binomial regression for differential expression with confounding factors 

具有混杂因子的差异表达的贝叶斯负二项式回归

 5.系统生物学

--Prediction of lncRNA–disease associations based on inductive matrix completion 

基于归纳矩阵完成的lncRNA-疾病关联预测
原文地址:https://www.cnblogs.com/BlueBlueSea/p/9745779.html