13 | ̼ | Prepare co-expression data using GEOquery package in R | TopicSem | |
18 | ̼ | Systematic detection of putative tumor suppressor genes through the combined use of exome and transcriptome sequencing | J.Club |
03 | ̼ | Exome and transcriptome sequencing data analysis | MAInfo | |
04 | ̼ | miRNA-mRNA Pair-database : summarize by 4 categories | TopicSem | |
25 | ̼ | miRNA target prediction and functional annotation | Seminar |
08 | ̼ | miRNA-mRNA pair database fill out statistics | TopicSem | |
31 | ̼ | SeqGene a comprehensive software solution for mining exome- and transcriptome- sequencing data | J.Club |
22 | ̼ | Genomic similarity in population | MAInfo |
23 | ̼ | RNA-seq Data Analysis | TopicSem |
16 | ̼ | MU2A - reconciling the genome and transcriptome to determine the effects of base substitutions | J.Club |
07 | ̼ | Sequence comparison in population | MAInfo | |
13 | ̼ | MicroRNA м miRNA-mRNA Ӽ ͺ̽ м | TopicSem | |
20 | ̼ | MicroRNA м microRNA-mRNA Ӽ ͺ̽ м | TopicSem |
06 | ̼ | miRNA-mRNA pair database design | TopicSem | |
09 | ̼ | Towards computational prediction of microRNA function and activity | J.Club |
16 | ̼ | To analysis co-transcriptomics data using miRNA-mRNA pairing database | TopicSem | |
29 | ̼ | Differential expression analysis for sequence count data | MAInfo |
05 | ̼ | Database of miRNA-mRNA pairs | TopicSem | |
26 | ̼ | miRNA-mRNA pairing relationship ? genomic locations and co-transcriptomics data set | TopicSem |
16 | ̼ | Mapping and quantifying mammalian transcriptomes | MAInfo | |
30 | ̼ | Read Count Normalization | MAInfo |
09 | ̼ | Purpose of Convert NGS reads into tags | Seminar | |
31 | ̼ | converting RNA-seq into tagCount compare with traditional extracting expression profile | MAInfo |
06 | ̼ | Apollo: a sequence annotation editor | MAInfo | |
06 | ̼ | DDBJ Read Archive and DDBJ Read Annotation Pipeline : an archive database and an analytical tool for next-generation sequence data | MAInfo | |
12 | ̼ | MAQ | MAInfo | |
14 | ̼ | add personal data | MAInfo | |
16 | ̼ | maq result using human Refseq data download | MAInfo | |
20 | ̼ | NGS and co-transcriptomics | MAInfo | |
24 | ̼ | Cepred: Predicting the Co-Expression Patterns of the Human Intronic microRNAs with Their Host Genes | J.Club | |
27 | ̼ | A highly annotated whole-genome sequence of a Korean Indivisual | MAInfo |
08 | ̼ | Plan for NGS Data replications | Seminar | |
22 | ̼ | Progress in NGS data analysis - complete preprocessing | Seminar |
30 | ̼ | Targeted next-generation sequencing of a cancer transcriptome enhances detection of sequence variants and novel fusion transcripts | J.Club |
15 | ̼ | GO annotation for clustered miRNAs | Seminar | |
17 | ̼ | Evaluating DNA Sequence Variants of Unknown Biological Significance | BookReading | |
20 | ̼ | GeneSet2miRNA: finding the signature of cooperative miRNA activities in the gene lists | J.Club |
06 | ̼ | Osteoporosis Data Analysis - | Seminar | |
23 | ̼ | Stem cell miRNA microarray analysis | Seminar |
16 | ̼ | Predict miRNA expression profiles from mRNA expressions using machine learning - purpose of this study | Seminar | |
28 | ̼ | Comparison of normalization methods with microRNA microarray | J.Club |
08 | ̼ | Compare the clustering performance using mRNA/miRNA expression profiles | Seminar | |
29 | ̼ | Predict microRNA expression profiles from mRNA expressions using NN | Seminar |
02 | ̼ | CCD | Seminar | |
03 | ̼ | Computational analysis of biological functions and pathways | J.Club | |
23 | ̼ | co-regulation btw miRNA and mRNA | Seminar | |
31 | ̼ | The microRNA.org resource:targets and expression | J.Club |
05 | ̼ | MicroRNA acuurately identify cancer tissue origin | J.Club | |
18 | ̼ | ڷ miRNA м | Seminar |
14 | ̼ | Mining co-regulated gene profiles for the detection of functional associations in gene expression data | Seminar | |
31 | ̼ | N2a microRNA | Seminar |
23 | ̼ | A comparison of meta-analysis methods for detecting differentially expressed genes in microarray experiments | J.Club | |
26 | ̼ | Mining co-regulated genes | Seminar |
13 | ̼ | Feature selection and classification of time series microarray using GP 2nd idea | Seminar |
01 | ̼ | GPDTI A Genetic Programming Decision Tree Induction method to find epistatic effects in common complex diseases | J.Club | |
18 | ̼ | Microarray Feature Selection using GP | Seminar |
10 | ̼ | Data analysis ,CCD data | Seminar | |
31 | ̼ | ISMB2007 Review - microarray | Seminar |
07 | ̼ | maSigPro: a Method to Identify Significantly Differential Expression Profiles in Time-Course Microarray Experiments | J.Club | |
11 | ̼ | CCD м Ȳ | Seminar | |
27 | ̼ | Seminar |
01 | ̼ | CCD м ȹ | Seminar | |
16 | ̼ | Significance analysis of mcroarray transcript levels in time series experiments | J.Club | |
22 | ̼ | CCD м | Seminar |
28 | ̼ | Modeling Nonlinearity in Dilution Design Microarray Data [microarray, dilution] | J.Club |
10 | ̼ | A Five-Gene Signature and Clinical Outcome in Non-Small-Cell Lung Cancer | J.Club |
01 | ̼ | 縯 ۸ м | MAInfo | |
28 | ̼ | ۸ м ABI м | xMutant |
12 | ̼ | ü м | xMutant | |
20 | ̼ | ENU м | MAInfo |
02 | ̼ | AB microarray м(2) | MAInfo | |
04 | ̼ | NA | xMutant | |
23 | ̼ | ABI chip м Ȳ (2-way ANOVA ̿ Gene Filtering۾) | MAInfo |
14 | ̼ | A comparison of normalization methods for high density oligonucleotide array data based on variance and bias | J.Club |
05 | ̼ | Ontologizer Review | MAInfo | |
26 | ̼ | AB microarray м | MAInfo | |
29 | ̼ | AB microarray м [MAInfo] | Seminar |
15 | ̼ | Normalization microarray м | MAInfo |
17 | ̼ | Research plan | MAInfo |
13 | ̼ | A genetic Approach for Gene Selection on Microarray Expression data | MAInfo |