|
Date
Members |
| 04 | ̿ | Process of Register Sequence data in Public Repository | |
| 15 | 권호식 | Propensity score analysis and R packages |
| 07 | ̿ | Triple Negative Breast Cancer TMB Analysis |
| 02 | 최선 | Handling temporality of clinical events with application to Adverse Drug Event detection in Electronic Health Records: A scoping review | |
| 9 | ̿ | Result of BRCA2 CNV qPCR Validation |
| 14 | 최선 | Basic operation of Flask | |
| 17 | ̿ | Triple Negative Breast Cancer Analysis | |
| 28 | 권호식 | review : Oligonucleotide microarray |
| 10 | ̿ | NGS CheckMate : Validating sample identity in NGS studies |
| 06 | ̿ | Somatic Mutation Filtering Result with Korea1KG | |
| 20 | 권호식 | Error and Trouble shooting In TVC and GATK | |
| 20 | 유경훈 | Perturbation robustness analyses reveal parameters in variant interpretation pipelines |
| 06 | 최선 | Query design for emr study& | |
| 06 | 최선 | Query design for emr study& | |
| 20 | Helix UK Biobank browser | ||
| 27 | Study overview of post ERCP pancreatitis |
| 05 | The all of us research program | ||
| 19 | Analysis of genetic and clinical data in AML patients with prolonged neutropenia | ||
| 26 | ̿ | GDC Tumor Only Variant Calling Pipeline with Uveal Melanoma |
| 01 | 유경훈 | A robust benchmark for germline structural variant detection | |
| 08 | 권호식 | Markers related with Iopromide from Literatures |
| 13 | 유경훈 | A benchmark study of scoring methods for non-coding mutations. | |
| 20 | 권호식 | Review : Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls | |
| 27 | 최선 | rehab-CDM |
| 14 | 권호식 | Clinical data of HD-MTX samples | |
| 21 | 채정환 | taxol study_tcga data | |
| 28 | Difference of genetic architectures in men and women with depression |
| 12 | 유승원 | discussion : strategies for identification of read errors during Ion Proton based sequencing file calling workflow |
| 04 | 권호식 | KOVA : Korean Variant Archive | |
| 11 | 채정환 | taxol-ADR data analysis(FDR/OR statistics) | |
| 18 | Reviewing the clinical utility of polygenic risk score |
| 01 | WXS for leukemia busulfan-VOD | ||
| 08 | 유승원 | Work flow discussion | |
| 15 | 유경훈 | Patients subgrouping by antidepressant prescription | |
| 29 | 채정환 | review; Introduction to bioinformatics algorithms |
| 07 | ̿ | Comparing Gene Fusion Detection Algorithm with WGS | |
| 07 | ̿ | Comparing Gene Fusion Detection Algorithm with WGS | |
| 14 | ӿ | Project DRIVE: deep RNAi interrogation of viability effects in cancer | |
| 21 | Inference of candidate Synthetic Cytotoxic Drug (Pyrimethamine, Paclitaxel) | ||
| 28 | The charactericstics of singleton variants in neuropsychiatric disorders |
| 12 | SATIE: a web tool to predict sequential treatments in cancer. | ||
| 19 | Prognostic power of RUD (relative usage of distal poly(A) sites) | ||
| 26 | ̿ | Comparison of Adapter Trimmers for Illumina Miseq Data |
| 03 | ̿ | Improved VCF Nomralization | |
| 10 | ӿ | PARP inhibitors: Synthetic lethality in the clinic | |
| 17 | Classification and segmentation in convolutional neural network | ||
| 31 | Identifying personalized candidate genes using case-control score distribution dissimilarity |
| 01 | The review of variant analysis tool, Sequence To Medical Phenotypes | ||
| 08 | ̿ | Package for analysing cancer panel data | |
| 22 | How to use MuTect, ExomeCNV and EXPANDS. |
| 03 | Overexpression using normal expression in SDL analysis | ||
| 13 | Preprocessing and QC results of 27 BronJ WXSs. |
| 07 | The distribution of association with gene and disease according to PPI degree | ||
| 15 | ӿ | The Human Phenotype Ontology (HPO) | |
| 21 | Synthetic dosage lethality in LUAD |
| 06 | GMOD JBrowse Genome Browser Settings and Configuration | ||
| 14 | ӿ | Overview of Gene Ontology and its application | |
| 20 | Systematic meta-analyses of Alzheimer disease genetic association studies |
| 03 | 躸 | TCGA Protected Mutation Description | |
| 10 | Proton Sequencing Data Preprocessing and Pipeline | ||
| 17 | Proton Sequencing Data Alignment Result with BWA | ||
| 24 | Proton Sequencing Data, Unmapped Region |
| 04 | Mutational analysis in 12 Tumor type | ||
| 11 | ӿ | Identification of synthetic lethal genes in 12 major cancer types |
| 08 | Sorting Tolerant From Intolerant Algorithm and its scores | ||
| 18 | Screening of association between marker SNPs and gene score | ||
| 22 | The number of Ensembl gene IDs in SIFT DB and Ensembl DB |
| 07 | TCGA Data Assess Page: Downloadable Link and Specification | ||
| 14 | ӿ | Resources for Cancer Genome: COSMIC | |
| 30 | ӿ | Patterns of Methylation Status and Somatic mutations in Cancer Genome |
| 19 | Analysis of TCGA Data Structure: What is in the downloaded files? | ||
| 19 | Analysis of TCGA Data Structure: What is in the downloaded files? | ||
| 26 | ӿ | DNA Methylation in TCGA Data and its Structure. |
| 10 | Clinical data analysis for COPD | ||
| 22 | Selection of drug list used in Medcassandra and distribution of damaged drug and gene score |
| 04 | Predicting disease predisposition patterns of the personal genome | ||
| 18 | Adjustment of drug and ADR ranking using 1000genome |
| 06 | ̼ | Network Biology and Medicine team topic summary | |
| 13 | Statistics and improvement of drug and ADR ranking | ||
| 29 | genetic interaction for breast cancer | ||
| 29 | genetic interaction for breast cancer |
| 30 | A genome-wide genetic interactions map for breast cancer survival |
| 10 | improvement way of ADR ranking algorithm | ||
| 17 | Modified results of Phenotype drug-drug interaction | ||
| 28 | analysis of epistatic interaction for breast cancer survival |
| 05 | Network result of phenotypic drug drug interaction | ||
| 12 | ̼ | Drug-Side effect Network construction using nursing statement and lab data. |
| 02 | ̼ | Drug-Side effect network design and pre analysis result | |
| 27 | ȭ | Network approach for identifying oncogenic processes and candidate driver genes in colorectal cancer | |
| 08 | Rocky | NCI-60 Cell lines experimental condition and genes expression profiles and drugs sensitivity analysis |
| 06 | Rocky | Global impact on genomic variations in microRNAs, target genes and drug relationship | |
| 27 | Construct a Network with Personal Variants. |
| 15 | Rocky | [Replication- Work Progress] - Comprehensive analysis of the impact of SNPs and CNVs on human microRNAs and their regulatory genes | |
| 22 | Pharmacology network for drug repositioning |
| 04 | Construct a Network Linking Personal Variations | ||
| 18 | ̼S | GEE ۾ ô Ȳ ߰ ۾ |
| 02 | 赵 | What is TCGA? | |
| 09 | 赵 | Brainstorming on Integrative Genome Informatics (Research Topics from each member) | |
| 23 | 赵 | Brainstorming on Network biology and medicine |
| 08 | ̼S | test | |
| 10 | Rocky | GEOquery | |
| 16 | Rocky | GEOquery test | |
| 24 | ̼ | MARQ: an online tool to mine GEO for experiments with similar or opposite gene expression signatures | |
| 31 | Rocky | GEOquery test |
| 21 | ̼S | aa |
| 07 | ̼S | Keyword search for Microarray data using evoc term as stemmng | |
| 10 | Rocky | BioPortal: A Web Repository for Biomedical Ontologies and Data | |
| 15 | Rocky | Gene Expression Omnibus (GEO) |
| 05 | Rocky | MAGE-TAB VS MINiML | |
| 07 | ̼S | 1107 | |
| 12 | ̼S | porter stemming | |
| 12 | ̼S | porter stemming | |
| 12 | ̼ | idf parsing result | |
| 19 | ̼S | Keyword search for Microarray data using evoc term as stemming | |
| 19 | Rocky | Attributes list comparison for MAGE-TAB / MINiML |
| 01 | distinct EV_term list | ||
| 01 | distinct synonym list | |
|
| 01 | ̼ | DB Design _0.1 | |
| 05 | Rocky | table format | |
| 05 | ̼S | SDRF-ADF-IDF relation | |
| 15 | Rocky | Parsing headers for adf.txt and unique attributes from sdrf and adf.txt files | |
| 17 | ArrayExpress | |
|
| 20 | for Busan | ||
| 21 | Rocky | Parsing code for sdrf.txt attributes and extracting unique terms | |
| 24 | empty file list among adf text | ||
| 24 | error file list among adf text | ||
| 26 | ̼ | SDRF Distinct List | |
| 26 | ̼ | SDRF Full List | |
| 27 | Rocky | Extracting ArrayExpress sdrf/adf/idf unique terms | |
| 29 | ArrayExpress adf files | ||
| 31 | adf relation |
| 07 | ArrayExpress down | ||
| 17 | ̼S | conversion SOFT to MAGE-TAB | |
| 17 | Rocky | eVOC mapping idea | |
| 06 | ̼S | Make rules for conversion SOFT to MAGE-TAB | |
| 06 | 赵2 | ||
| 09 | Rocky | The MGED Ontology - Its Structure and Standards | |
| 30 | ̼S | make a rule |
| 05 | Progress in B10 data analysis | ||
| 12 | Primary schema & Extended schemata status [Platform, GEO feature, mapping] | ||
| 19 | α | time series microarray м [[time-series]] |
| 03 | CC2Path progress | ||
| 03 | CTMS (Clinical Trial Management System) ȹ | ||
| 10 | TG2-Knockout mouse Data Analysis | |
|
| 10 | Breastome : Meta-analytic approach of breast cancer | ||
| 17 | Progress in clustering column of GEO data table : Platform [GEO, Platform, data matix, column] | ||
| 17 | α | Coexpression dynamics | |
| 24 | Mantel test with weighted correlation | ||
| 24 | CC2Path |
| 08 | α | spm | |
| 08 | ϼ EMR ڷ м | ||
| 15 | Integration of Mantel test & MDR algorithm | ||
| 15 | PahtMeSH + miRNA progress | ||
| 22 | GEO localization | ||
| 29 | α | Interpretation of inter-module relationship in SPM | |
| 29 | Progress in Cybrid data analysis | |
| 06 | Data Analysis: Hepatocelluar Carcinoma Data | ||
| 06 | GOChase 2 progress - (manuscript & web interface) | ||
| 13 | Construction of GRIP | ||
| 13 | Analysis of Hapatocellular Carcinoma Data | ||
| 27 | ü DB |
| 05 | Gene Identifier ο ִ idea | ||
| 05 | An error in using FDR | ||
| 12 | α | terminal GO ð ߷ | |
| 12 | GOChase 2 progress (web interface) | ||
| 19 | Hepatocelluar carcinoma data analysis : Preprocessing | ||
| 19 | Scoring of clustered data using Mutual Information | ||
| 26 | Identification of Pathways related to Pathologic Status in Lung cancer using Global Test | ||
| 26 |
| 12 | ̼ | ü м | |
| 12 | [Plan]Extension of Venn Diagram | ||
| 19 | Progress of GOChase 2- Error (redundant and inconsistent annotation error) confirm | ||
| 26 | PathTalk: the second step [PathTalk] |
| 04 | ¼ | Secondary analysis of arrary CGH data | |
| 04 | NA | ||
| 18 | α | NA | |
| 25 | Analysis of gastric cancer tissue microarray data |
| 07 | BAC Clones resolved | ||
| 07 | object model and relational database for tissue microarray | ||
| 14 | ¼ | array CGH data analysis | |
| 14 | NA | ||
| 21 | NA | ||
| 21 | α | NA | |
| 28 | Web based ArrayCGH data analysis tool (1/2) | ||
| 28 | NA |
| 03 | MIAME/Onc | ||
| 03 | GOFCA- apply cell cycle data and liver cancer data - | ||
| 10 | ̼ȣ | BioCandi : Further Plan | |
| 10 | α | NA | |
| 17 | NA | ||
| 24 | NA | ||
| 24 | Comparison of XPERANTO and mAdb | ||
| 31 | NA | ||
| 31 | α | NA |
| 05 | NA | ||
| 05 | PathFCA: applied Mouse Kidney Data | ||
| 12 | ȭ | Clinical-Genomic integration within CDA - INTRO. | |
| 12 | NA | ||
| 19 | ̼ȣ | NA | |
| 26 | PK Profile ý | ||
| 26 | ü genotype data human whole genome mapping display ϱ |
| 17 | α | The Biginning | |
| 24 | Beginning of AppGen |