BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Bioinformatics Software | QIAGEN Digital Insights - ECPv6.16.2//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://staging.digitalinsights.supremeclients.com
X-WR-CALDESC:Events for Bioinformatics Software | QIAGEN Digital Insights
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Halifax
BEGIN:DAYLIGHT
TZOFFSETFROM:-0400
TZOFFSETTO:-0300
TZNAME:ADT
DTSTART:20230312T060000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0300
TZOFFSETTO:-0400
TZNAME:AST
DTSTART:20231105T050000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0400
TZOFFSETTO:-0300
TZNAME:ADT
DTSTART:20240310T060000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0300
TZOFFSETTO:-0400
TZNAME:AST
DTSTART:20241103T050000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0400
TZOFFSETTO:-0300
TZNAME:ADT
DTSTART:20250309T060000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0300
TZOFFSETTO:-0400
TZNAME:AST
DTSTART:20251102T050000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Halifax:20240801T130000
DTEND;TZID=America/Halifax:20240801T140000
DTSTAMP:20260610T224157
CREATED:20240723T210121Z
LAST-MODIFIED:20241024T183050Z
UID:10000779-1722517200-1722520800@staging.digitalinsights.supremeclients.com
SUMMARY:Discovery from sample-level public data (GEO\, SRA and more) using IPA Land Explorer
DESCRIPTION:Within QIAGEN Ingenuity Pathway Analysis (IPA)\, public data sourced from OmicSoft is already processed and standardized\, making it easy to jump to the actual research. In this training\, we'll show how to effectively use sample-level public data and metadata from sources like GEO\, SRA\, TCGA\, GTEx\, Blueprint\, CCLE and other sources using the IPA Analysis Match and Land Explorer features. We will walk through various use cases\, such as biomarker discovery\, drug target investigation\, studying survival in custom patient cohorts\, multi-gene correlation and more. \nYou will learn to answer questions such as: \n\nHow is a gene of interest expressed across different conditions (e.g. diseases\, treatments\, cell lines)?\nIs there correlation in the expression for two genes or biomarkers of user interest for a given condition?\nFor a given condition of interest\, can we derive a list of genes (e.g.\, genes specific to a disease\, treatment or cell type)?\nCan we generate custom cohorts of patients (e.g.\, example TP53 wt vs mutant or PDCD1 high vs low expression) and then\, generate survival curves representing those cohorts? Can we generate p-values to see if there is significant difference?\nCan we detect expression of a gene in different cell types from single cell data?
URL:https://staging.digitalinsights.supremeclients.com/webinars-and-events/discovery-from-sample-level-public-data-geo-sra-and-more-using-ipa-land-explorer/
LOCATION:Virtual - Americas - EST\, United States
CATEGORIES:Discovery,Webinar
ATTACH;FMTTYPE=image/jpeg:https://staging.digitalinsights.supremeclients.com/wp-content/uploads/2024/05/S_9978_QDI_IPA_Gi609807396_16x9_Medium-720px_50570.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Halifax:20240801T130000
DTEND;TZID=America/Halifax:20240801T140000
DTSTAMP:20260610T224157
CREATED:20240808T095712Z
LAST-MODIFIED:20241024T182420Z
UID:10000549-1722517200-1722520800@staging.digitalinsights.supremeclients.com
SUMMARY:Discovery from sample-level public data (GEO\, SRA and more) using IPA Land Explorer
DESCRIPTION:Within QIAGEN Ingenuity Pathway Analysis (IPA)\, public data sourced from OmicSoft is already processed and standardized\, making it easy to jump to the actual research. In this training\, we'll show how to effectively use sample-level public data and metadata from sources like GEO\, SRA\, TCGA\, GTEx\, Blueprint\, CCLE and other sources using the IPA Analysis Match and Land Explorer features. We will walk through various use cases\, such as biomarker discovery\, drug target investigation\, studying survival in custom patient cohorts\, multi-gene correlation and more. \nYou will learn to answer questions such as: \n\nHow is a gene of interest expressed across different conditions (e.g. diseases\, treatments\, cell lines)?\nIs there correlation in the expression for two genes or biomarkers of user interest for a given condition?\nFor a given condition of interest\, can we derive a list of genes (e.g.\, genes specific to a disease\, treatment or cell type)?\nCan we generate custom cohorts of patients (e.g.\, example TP53 wt vs mutant or PDCD1 high vs low expression) and then\, generate survival curves representing those cohorts? Can we generate p-values to see if there is significant difference?\nCan we detect expression of a gene in different cell types from single cell data?
URL:https://staging.digitalinsights.supremeclients.com/webinars-and-events/discovery-from-sample-level-public-data-geo-sra-and-more-using-ipa-land-explorer-2/
LOCATION:HSMD-screen-grab-2
ATTACH;FMTTYPE=image/jpeg:https://staging.digitalinsights.supremeclients.com/wp-content/uploads/2024/08/S_9978_QDI_IPA_Gi609807396_16x9_Medium-720px_50570-5.jpg
END:VEVENT
END:VCALENDAR