SNUBI Research ::   (163 talks satisfying Presenter = 김기태)
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2019-06:
03 김기태   TopicSem
15 김기태   J.Club

2019-05:
09 김기태 GSDBA: Computational approach for Gene Set wise Deleterious Burden Analysis   TopicSem
20 김기태 Parallel processing in R   SysBiol
23 김기태 Parallel processing in R   MAInfo

2019-04:
04 김기태 GS-DBA: Gene Set Deleterious Burden Analysis  MAInfo

2019-03:
21 김기태 GS-DBA: Gene Set Deleterious Burden Analysis  TopicSem
30 김기태 Pathway Based Analysis of Mutation Data Is Efficient for Scoring Target Cancer Drugs     J.Club

2019-02:
07 김기태 Consensus Path DB  SysBiol
11 김기태 Analysis of Age at onset in MDD : Optimizing the cut-off   TopicSem

2019-01:
03 김기태 Analysis of early response in MDD: Additional variant level analysis   TopicSem
17 김기태 Analysis of age at onset in depression  MAInfo
26 김기태 Efficiient Parameter Estimation Enables the Prediction of Drug Response Using a Mechanistic Pan-Cancer Pathway Model     J.Club

2018-12:
06 김기태 Analysis of Early response in depression  SysBiol
26 김기태 Dopaminergic and noradrenergic system, Neurotransmission and Brain-related genes are associated with treatment response in 1,000 Korean patients with Major Depressive Disorder.   Seminar

2018-11:
05 김기태 er  Seminar
24 김기태 Pathway-structured predictive modeling for multi-level drug response in multiple myeloma     J.Club
29 김기태 Analysis of early response in depression  TopicSem

2018-10:
11 김기태 Geneset Deleterious Burden Analysis (GS-DBA)  SysBiol
18 김기태 Analysis of onset age in depression  MAInfo
23 김기태 AOS in MDD  Seminar
23 김기태 EarlyResponse  Seminar
29 김기태 Analysis of Early response in depression  TopicSem

2018-09:
08 김기태 Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines     J.Club
12 김기태 depression  Seminar
20 김기태 Analysis of Early response in depression  TopicSem
20 김기태 우울증회의자료  Seminar

2018-08:
13 김기태 Analysis of Early response in depression  TopicSem
16 김기태 Age of onset in MDD  SysBiol
20 김기태 [Review]Variant caller  MAInfo
30 김기태 회의자료  Seminar

2018-07:
15 김기태 임시파일  Seminar
16 김기태 Analysis of Early response in depression  TopicSem
21 김기태 Relationship between Deleterious Variation, Genomic Autozygosity, and Disease Risk: Insights from The 1000 Genomes Project     J.Club

2018-06:
18 김기태 Analysis of Early response in depression  TopicSem
25 김기태 UCSC Xena:Analysis tools for cancer   MAInfo

2018-05:
10 김기태 Analysis of response in depression : EN-RN vs. EY-RY  TopicSem
16 김기태 EN-RNvs.EY-RYanalysis in depression  MAInfo
16 김기태 ENvs.EYanalysis in depression  MAInfo
16 김기태 summary  MAInfo

2018-04:
02 김기태 Prediction of response in depression  TopicSem
19 김기태 Analysis of onset age in depression  SysBiol
19 김기태 Analysis of onset age in depression_meet  SysBiol
28 김기태 An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics     J.Club

2018-03:
28 김기태 iCAGES:integrated Cancer GEnome Score for comprehensively prioritizing driver genes in personal cancer genomes  MAInfo

2018-02:
01 김기태 Prediction model of treatment response in depression   MAInfo
03 김기태 A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles     J.Club
12 김기태 Prediction model for response in depression  TopicSem

2018-01:
15 김기태 Prediction model for 12 week remission in depression  TopicSem

2017-12:
02 김기태 Discovering novel pharmacogenomic biomarkers by imputing drug response in cancer patients from large genomics studies     J.Club
11 김기태 Analysis of depression between early and later onset  TopicSem
20 김기태 Analysis of depression with cut-off in age of onset   MAInfo

2017-11:
01 김기태 Ependymal tumor analysis  MAInfo
13 김기태 Analysis of 1000 depressive  TopicSem

2017-09:
04 김기태 Analysis of Ependymal tumor  TopicSem
06 김기태 Analysis of microarray using the GEO data   MAInfo
16 김기태 Using Clinical Characteristics to Identify Which Patients With Major Depressive Disorder Have a Higher Genetic Load for Three Psychiatric Disorders     J.Club
27 김기태 Analysis with pathway score in 999 Depressive patients  TopicSem

2017-07:
01 김기태 AACR Project GENIE: Powering Precision Medicine Through An International Consortium     J.Club
05 김기태 GENIE : Basic characteristics of clinical and genomic data across the various cancer type  MAInfo
24 김기태  Pathway score for survival analysis in HNSC   TopicSem

2017-06:
19 김기태 Survival analysis in HNSC with metabolism pathway - Interpretation of the result  TopicSem

2017-05:
13 김기태 Pathway-Structured Predictive Model for Cancer Survival Prediction: A Two-Stage Approach     J.Club
17 김기태 Survival analysis with pathway score in metabolism pathways  TopicSem

2017-04:
10 김기태 Pathway score based on the gene damaging score  TopicSem

2017-03:
06 김기태 Pathway score based on the gene damaging score  TopicSem
08 김기태 MEREDITH:Clustering and Visualization tools for TCGA PAN-CANCER with multiplatform genomic data  MAInfo

2017-02:
25 김기태 Pathway-based gene signatures predicting clinical outcome of lung adenocarcinoma     J.Club

2017-01:
11 김기태 Pathway damaging score based on the gene score in the Head and Neck squamous cell carcinomas   TopicSem
11 김기태 [Review]Pathway based gene signature predicting clinical outcome in cancer  MAInfo
11 김기태 [Review]Pathway based gene signature predicting clinical outcome in cancer  MAInfo

2016-12:
07 김기태 Pathway damaging score based on the gene score in the Head and Neck squamous cell carcinomas   TopicSem
30 김기태 Pathway damaging score based on the gene score in the Head and Neck squamous cell carcinomas   Seminar

2016-11:
16 김기태 [Review] Filtering variant and Direction of effect in SKAT-O test  MAInfo
26 김기태 A new correlation clustering method for cancer mutation analysis     J.Club

2016-10:
31 김기태 WXS analysis in COPD patients with LABA/LAMA treatment  TopicSem

2016-09:
12 김기태 WXS analysis in COPD patients with LABA/LAMA treatment  TopicSem
21 김기태 [Review]Towards precision medicine   MAInfo

2016-08:
10 김기태 [review]Personalized pathway enrichment map   MAInfo
19 김기태 Identifying the functional target using the combination of genes across the multiple carcinomas  Seminar
27 김기태 Identifying overlapping mutated driver pathways by constructing gene networks in cancer.     J.Club

2016-07:
02 김기태 An integrative somatic mutation analysis to identify pathways linked with survival outcomes across 19 cancer types     J.Club
27 김기태 Methodology for the identifying the functional target across the carcinomas (squamous cell carcinomas)   TopicSem

2016-06:
10 김기태 Analysis of WXS data in COPD patients  MAInfo
22 김기태 WXS analysis in COPD patients with LABA/LAMA treatment  TopicSem

2016-05:
16 김기태 Methodology for the identifying the functional target across the carcinomas (squamous cell carcinomas)  TopicSem

2016-04:
06 김기태 Methodology for the identifying the functional target across the carcinomas (squamous cell carcinomas)   TopicSem
16 김기태 Cancer type-dependent genetic interactions between cancer driver alterations indicate plasticity of epistasis across cell types     J.Club
22 김기태 Review of cancer subtypes with molecular characters (LGG,KIRC,LAML)  MAInfo

2016-03:
18 김기태 molecular clinico feature   MAInfo

2015-10:
07 김기태   TopicSem

2015-08:
19 김기태 Identifying the clinical implication of the genetic combinatory factors across the squamous cell carcinomas  TopicSem
29 김기태 Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas     J.Club

2015-07:
15 김기태 Decision and Revision on the FAT1 study  TopicSem

2015-06:
13 김기태 Somatic mutations in arachidonic acid metabolism pathway genes enhance oral cancer post-treatment disease-free survival      J.Club
17 김기태 Functional pathway based approach for identifying the cancer prognostic signature  TopicSem

2015-05:
13 김기태 Somatic mutation based approach for identifying the cancer prognostic signature  TopicSem

2015-04:
04 김기태 Uncovering disease-disease relationships through the incomplete interactome     J.Club
13 김기태 Identifying the prognostic event in the Carcinomas sharing histopahtology  TopicSem
24 김기태 Pathway enrichment analysis using the Reactome Functional interaction module of Cytoscape  xMutant

2015-03:
09 김기태 Review of National Cancer Institute Data catalog   TopicSem
20 김기태 Confounding factor of clinical characteristics in the multivariate survival analysis  xMutant

2015-01:
09 김기태 Multivariate survival analysis with Cox-proportional hazard ratio model   xMutant
19 김기태 Association of FAT1 mutation with survival in HPV-negative patients with head and neck squamous cell carcinoma   TopicSem
24 김기태 Multi-tiered genomic analysis of head and neck cancer ties TP53 mutation to 3p loss     J.Club
26 김기태 SG07     Seminar

2014-12:
05 김기태 Error rate correction of multiple hypothesis test  xMutant
22 김기태 Somatic mutations of FAT1 in the Head and Neck Squamous cell Carcinoma  TopicSem
26 김기태 Human papillomavirus and survival in Cancer  xMutant

2014-11:
05 김기태 SG07 gene interpretation  Seminar
12 김기태 Relationship of Major Wnt pathway genes and 15 nmLoF genes in the SQCCs  TopicSem
29 김기태 Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin     J.Club

2014-10:
23 김기태 Mutation landscape graph in the SqCCs  xMutant

2014-09:
03 김기태 HPV status Data in the TCGA - Squamous cell carcinoma  xMutant
06 김기태 Integrative and comparative genomic analysis of HPV-positive and HPV-negative head and neck squamous cell carcinomas     J.Club
26 김기태 Dys-regulation of the Wnt pathway in the SQCCs   xMutant
29 김기태 Dys-regulation of the Wnt pathway in the squamous cell carcinoma  TopicSem

2014-08:
18 김기태 Mutation spectrum graph and Discussion in the SQCCs research  TopicSem

2014-07:
05 김기태 Network-based stratification of tumor mutations     J.Club
26 김기태 ISMB review : Simultaneously identification of multiple driver pathways in cancer  J.Club
30 김기태 Dysregulation of Wnt pathway in the HNSC and LUSC   TopicSem
30 김기태 Review-BioGrid :Database of protein and genetic interaction   xMutant

2014-06:
18 김기태 Survival analysis and Validation of the Mutated Wnt pathway genes in the SQCCs  TopicSem
19 김기태 Survival analysis and Validation of the Mutated Wnt pathway genes in the SQCCs  xMutant

2014-05:
03 김기태 Integrative and Comparative Genomic Analysis of Lung Squamous Cell Carcinomas in East Asian Patients     J.Club
21 김기태 Strategy of the mutation profile analysis in SQCCs  TopicSem
30 김기태 Somatic Mutation profile analysis in SQCCs  Seminar

2014-04:
16 김기태 Mutation profile analysis in SQCCs  TopicSem

2014-03:
08 김기태 Comprehensive identification of mutational cancer driver genes across 12 tumor types     J.Club
24 김기태 Mutation profile analysis of Squamous cell carcinoma in TCGA  TopicSem

2014-02:
04 김기태 Mutational analysis in 12 Tumor type  xMutant
19 김기태 Mutation analysis in TCGA  TopicSem

2014-01:
07 김기태 MuSic and Dendrix for mutational analysis using in TCGA datas   xMutant
27 김기태 Mutation analysis in TCGA datas (Replication)  TopicSem

2013-12:
02 김기태 Relative risk of Type2diabete in kare data  TopicSem
21 김기태 Mutational landscape and significance across 12 major cancer types  J.Club
30 김기태 Mutation analysis in TCGA datas   TopicSem
31 김기태 TCGA Mutational Landscape and Distribution Across 12 Tumors  xMutant

2013-11:
04 김기태 Relative risk of diseases in kare data  TopicSem

2013-10:
26 김기태 Germline variation in TP53 regulatory network genes associates with breast cancer survival and treatment outcome  J.Club

2013-09:
07 김기태 DrGaP: A Powerful Tool for Identifying Driver Genes and Pathways in Cancer Sequencing Studies     J.Club
09 김기태 Relation of germline mutation and cancer  TopicSem
10 김기태 Distributed computing for variants annotation  xMutant
24 김기태 Geometric mean of SIFT scores per Gene and Exon in Normal population  xMutant
30 김기태 Relation of germline mutation and cancer  TopicSem

2013-08:
14 김기태 Identifying disease variant in genotypic association   TopicSem

2013-07:
12 김기태 Identifying disease variants in genotypic association  Seminar
17 김기태 Identifying disease variant in genotypic association  TopicSem
18 김기태 GWAS of cancer   MAInfo
20 김기태 Comprehensive molecular characterization of clear cell renal cell carcinoma  J.Club

2013-06:
01 김기태 integrated genomic characterization of endometrial carcinoma  J.Club
19 김기태 Identifying disease variants in genotypic association  TopicSem

2013-05:
01 김기태 Identifying disease variants in genotypic association  TopicSem
02 김기태 Odds ratios of disase variants with gene-gene and/or gene-environmental interactions  MAInfo
27 김기태 Identifying disease variants in genotypic association  TopicSem

2013-04:
02 김기태 Somatic Muatation Data and its Structure  xMutant
16 김기태 Coding for TCGA data  xMutant
30 김기태 TCGA 명세서   xMutant
30 김기태 TCGA data specifications for multiple data types and platforms  xMutant

2013-03:
28 김기태 Current Trends in Proteomics  MAInfo
28 김기태 Current Trends in Proteomics  MAInfo
28 김기태 Current Trends in Proteomics  MAInfo

2012-01:
15 김기태 Review:OMIM(Tools for genomic analysis of a catalogued gene)  xMutant

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