08 | 안세환 | J.Club | ||
13 | 안세환 | TopicSem |
04 | 안세환 | J.Club | ||
16 | 안세환 | TopicSem |
01 | 안세환 | OEIS to OMOP CDM | TopicSem | |
22 | 안세환 | Converting OEIS to OMOP CDM | TopicSem |
11 | 안세환 | Comparing VAMP-seq and star alleles | TopicSem | |
30 | 안세환 | Empowering personalized pharmacogenomics with generative AI solutions | J.Club |
03 | 안세환 | Integrating rare genetic variants into DPYD pharmacogenetic testing may help preventing fluoropyrimidine-induced toxicity | J.Club | |
19 | 안세환 | Embedded System | TopicSem |
25 | 안세환 | TopicSem |
13 | 안세환 | Classification of star alleles based on haplogroups | TopicSem | |
25 | 안세환 | Deep mutational scanning of CYP2C19 reveals a substrate specificity-abundance tradeoff | J.Club |
07 | 안세환 | Structural variation of the coding and non-coding human pharmacogenome | J.Club | |
19 | 안세환 | Classification of star alleles by haplogroups | TopicSem |
18 | 안세환 | Star-allele associated haplogroups of 25 pharmacogenes | TopicSem |
03 | 안세환 | Constructing Haplogroups for Pharmacogenes | TopicSem | |
15 | 안세환 | PharmaGScore scores of compound genetic variant burden for psychiatric treatment optimization | J.Club |
08 | 안세환 | Identifications of associations between star alleles and haplogroups | TopicSem |
11 | 안세환 | Association between haplogroups and star-alleles | TopicSem | |
13 | 안세환 | A novel machine learning-based approach for the computational functional assessment of pharmacogenomic variants | J.Club |
08 | 안세환 | A unifying model to predict variable drug response for personalised medicine. | J.Club | |
17 | 안세환 | Distribution of haplogroups and star-alleles | TopicSem |
23 | 안세환 | Identifying associations between haplogroups and star-alleles | TopicSem |
05 | 안세환 | test | SysBiol | |
16 | 안세환 | TopicSem |
19 | 안세환 | Identify novel variants in haplogroup | TopicSem | |
31 | 안세환 | Evaluating the frequency and the impact of pharmacogenetic alleles in an ancestrally diverse Biobank population | J.Club |
14 | 안세환 | Enrichment analysis of haplogroups | TopicSem | |
19 | 안세환 | PharmaKU: A web-based tool aimed at improving outreach and clinical utility of pharmacogenomics | J.Club |
01 | 안세환 | Aldy 4:An efficient genotypes and star-allele caller for pharmacygenomics | J.Club | |
20 | 안세환 | Haplogrouping performance evaluation | TopicSem |
22 | 안세환 | Evaluate haplogrouping by star-allele | TopicSem |
01 | 안세환 | Evaluate haplogroups by populations | TopicSem |
09 | 안세환 | Evaluation of haplogroups in 25 pharmacogenes | TopicSem | |
16 | 안세환 | Summary of variants in 25 pharmacogenes | SysBiol |
07 | 안세환 | Evaluation of haplogrouping results | TopicSem | |
09 | 안세환 | Pharmacogenomic landscape of Indian population using whole genomes | J.Club |
05 | 안세환 | Massively parallel characterization of CYP2C9 variant enzyme activity and abundance | J.Club | |
14 | 안세환 | Association between haplogroups and star-alleles in 25 pharmacogenes | TopicSem |
17 | 안세환 | Haplogroups of 25 pharmacogenes | TopicSem |
08 | 안세환 | Phenotype prediction and characterization of 25 pharmacogenes in Thais from whole genome sequencing for clinical implementation | J.Club | |
13 | 안세환 | Enrichment analysis of TPMT haplogroups | TopicSem |
20 | 안세환 | TPMT haplogroups enrichment analysis | TopicSem | |
28 | 안세환 | TPMT star-alleles in high-coverage T1GP | SysBiol |
16 | 안세환 | Results of matching Health Showcase data with T1GP haplogroups | TopicSem | |
25 | 안세환 | High coverage whole genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios | J.Club |
19 | 안세환 | Hierarchical clustering of TPMT haplgroups | TopicSem | |
24 | 안세환 | TPMT star-alleles and haplogroups of Health Showcase data | SysBiol |
07 | 안세환 | Haplogroupswith hierarchical clustering | TopicSem |
08 | 안세환 | Genetic ancestry plays a central role in population pharmacogenomics | J.Club |
22 | 안세환 | Deleterious TPMT haplogroups in T1GP | TopicSem | |
27 | 안세환 | Calling star-alleles from NGS data | SysBiol |
04 | 안세환 | Introduction of Hail | TopicSem |
16 | 안세환 | A systematic comparison of pharmacogene star allele calling bioinformatics algorithm: a focus on CYP2D6 genotyping | J.Club | |
21 | 안세환 | Functional or Deleterious variants in each haplogroup | TopicSem |
16 | 안세환 | FSGPs with LINCS L1000 data | TopicSem |
06 | 안세환 | Interpretation significant cell- and drug-specific FSGPs | TopicSem | |
22 | 안세환 | Improving cell-specific drug connectivity mapping with collaborative filtering | J.Club |
02 | 안세환 | Interpretation FSGPs in activator group | TopicSem | |
02 | 안세환 | Interpretation FSGPs in activator group | TopicSem | |
06 | 안세환 | Significant FSGPs estimating FDR | BioEMR |
11 | 안세환 | Discovering FSGP using gene expression signature and fold change | TopicSem |
16 | 안세환 | Determining significant FSGP using permutation | TopicSem | |
23 | 안세환 | Discovering FSGP for UKBiobank | BioEMR |
13 | 안세환 | Visualize interpretable pattern from LINCS-L1000 | SysBiol |
07 | 안세환 | . | J.Club | |
23 | 안세환 | Streamlined analysis of LINCS L1000 data with the slinky package for R | BioEMR | |
30 | 안세환 | Discovering interpretable pattern from LINCS-L1000 data | TopicSem |
11 | 안세환 | Introduction to Genetic Algorithm | SysBiol | |
18 | 안세환 | Breast cancer(adenocarcinoma) data in L1000 | BioEMR | |
25 | 안세환 | Discovering significant and interpretable pattern from L1000 data | TopicSem |
02 | 안세환 | L1000 data overview | BioEMR | |
09 | 안세환 | Overview of L1000 data | TopicSem | |
16 | 안세환 | Subtype of Cell Lines in L1000 data | SysBiol |
03 | 안세환 | Errors in importing Leukemia Data | SysBiol | |
17 | 안세환 | Datasets in cBioPortal | BioEMR | |
24 | 안세환 | Importing Leukemia Dataset into cBioPortal | TopicSem |
08 | 안세환 | File Formats of cBioPortal | TopicSem | |
15 | 안세환 | Select available columns in cBioPortal mutation file | SysBiol |
07 | 안세환 | Importing sample data into cBioPortal | TopicSem | |
07 | 안세환 | File Formats for cBioPortal | SysBiol | |
25 | 안세환 | About cBioPortal on GDPortal | BioEMR |
23 | 안세환 | GenIO: a phenotype-genotype analysis web server for clinical genomics of rare diseases | J.Club |
21 | 안세환 | The Mutation Significance Cutoff(MSC) | TopicSem | |
21 | 안세환 | How to use cBioPortal in GDPortal | BioEMR |
05 | 안세환 | How to visualize protein domain in VVA | TopicSem |
06 | 안세환 | Add VEP data to VVA | TopicSem |
23 | 안세환 | Add knowledge bases to VVA plot | SysBiol | |
25 | 안세환 | Gene Graphics: a genomic neighborhood data visualization web application | J.Club |
02 | 안세환 | VVA plot using GDM | TopicSem | |
14 | 안세환 | Genome U-Plot:a whole genome visualization | J.Club | |
19 | 안세환 | Modify VVA part interface of GDM portal | BioEMR | |
30 | 안세환 | Modified VVA Interface | TopicSem |
07 | 안세환 | GDM and VVA | BioEMR | |
28 | 안세환 | Apply VVA to GDM | SysBiol |
03 | 안세환 | clinical data for VVA | BioEMR | |
10 | 안세환 | Knowledge Bases for VVA | SysBiol | |
31 | 안세환 | Add knowledge bases to VVA | TopicSem |
23 | 안세환 | Add advanced features to VVA | TopicSem |