boinformatics-2018-10-1-Directory

1. Genetic analysis

--using standard microbiome Reference groups to simplify beta-diversity analyses and facilitate independent validation

Simplifies β-diversity analysis and facilitates independent validation using standard microbial Group reference groups

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

Grouper: Graph-based clustering and annotations for improved analysis of the head -up Transcriptome

--modeling One thousand intron length distributions with Fitild

Modeling 1000 intron length distributions using Fitild

2. Sequence analysis

--in Silico read normalization using Set Multi-cover optimization

Computer read normalization using Set multi-override optimization

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

Pbrpredict-suite: A set of models for predicting the structural domain residues in peptide recognition in protein sequences

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

Lzw-kernel: Fast kernel for protein sequence classification using variable length code blocks of LZW compressors

3. Structural Bioinformatics

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

Gaprepairer: A server used to model structural gaps and validate them using topology analysis

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

High accuracy of protein contact prediction using full convolutional neural networks and minimum sequence features

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

Application of graph theory to protein structure: Curl Spiral Atlas

--MICAN-SQ:A sequential protein structure alignment program that's applicable to monomers and all types of oligomers

MICAN-SQ: Sequential protein structure alignment procedure for monomers and all types of oligomers

4. Gene Expression

--rwen:response-weighted Elastic net for prediction of chemosensitivity of cancer cell lines

Rwen: Response-weighted elastic nets for predicting chemical susceptibility of cancer cell lines

--two-phase differential expression analysis for single cell RNA-SEQ

Two-stage differential expression analysis of single cell rna-seq

--bayesian Negative binomial regression for differential expression with confounding factors

Bayesian negative two-term regression with differential expression of confounding factors

5. System Biology

--prediction of lncrna–disease associations based on inductive matrix completion

Correlation prediction of lncrna-disease based on inductive matrix completion

boinformatics-2018-10-1-Directory