�ݺ�ߣshows by User: adeslat

�ݺ�ߣshows by User: adeslat / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: adeslat / Fri, 25 Jan 2019 16:24:31 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: adeslat Jax bio dataworldcongress.ngs.20181128finalwithoutbu /adeslat/jax-bio-dataworldcongressngs20181128finalwithoutbu jaxbiodataworldcongress-190125162431
NGS: How what we are measuring impacts data models and implications for data commons. New sequencing technologies, such as long read transcriptomic sequencing, gives us new gene models. These gene models alter the way we see past sequencing data and impacts how we assess the biological relevance of results. The disruption this causes to our view of the biological systems under study needs to be absorbed validated and the new view built upon. Understanding the lifecycle of data, the measurement technologies is imperative. Ultimately, statements, in sights may be the most long lived item. Claims validated by experiments and re-validated in every new context. Ultimately, old measurement technologies may go by way of the kilogram, replaced by reproducible experiments. What do we need to do to ensure that the persistent data stores upon which we rely enable this, promote this and enable us to become better data stewards.]]>
NGS: How what we are measuring impacts data models and implications for data commons. New sequencing technologies, such as long read transcriptomic sequencing, gives us new gene models. These gene models alter the way we see past sequencing data and impacts how we assess the biological relevance of results. The disruption this causes to our view of the biological systems under study needs to be absorbed validated and the new view built upon. Understanding the lifecycle of data, the measurement technologies is imperative. Ultimately, statements, in sights may be the most long lived item. Claims validated by experiments and re-validated in every new context. Ultimately, old measurement technologies may go by way of the kilogram, replaced by reproducible experiments. What do we need to do to ensure that the persistent data stores upon which we rely enable this, promote this and enable us to become better data stewards.]]> Fri, 25 Jan 2019 16:24:31 GMT /adeslat/jax-bio-dataworldcongressngs20181128finalwithoutbu adeslat@slideshare.net(adeslat) Jax bio dataworldcongress.ngs.20181128finalwithoutbu adeslat NGS: How what we are measuring impacts data models and implications for data commons. New sequencing technologies, such as long read transcriptomic sequencing, gives us new gene models. These gene models alter the way we see past sequencing data and impacts how we assess the biological relevance of results. The disruption this causes to our view of the biological systems under study needs to be absorbed validated and the new view built upon. Understanding the lifecycle of data, the measurement technologies is imperative. Ultimately, statements, in sights may be the most long lived item. Claims validated by experiments and re-validated in every new context. Ultimately, old measurement technologies may go by way of the kilogram, replaced by reproducible experiments. What do we need to do to ensure that the persistent data stores upon which we rely enable this, promote this and enable us to become better data stewards. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/jaxbiodataworldcongress-190125162431-thumbnail.jpg?width=120&height=120&fit=bounds" /> NGS: How what we are measuring impacts data models and implications for data commons. New sequencing technologies, such as long read transcriptomic sequencing, gives us new gene models. These gene models alter the way we see past sequencing data and impacts how we assess the biological relevance of results. The disruption this causes to our view of the biological systems under study needs to be absorbed validated and the new view built upon. Understanding the lifecycle of data, the measurement technologies is imperative. Ultimately, statements, in sights may be the most long lived item. Claims validated by experiments and re-validated in every new context. Ultimately, old measurement technologies may go by way of the kilogram, replaced by reproducible experiments. What do we need to do to ensure that the persistent data stores upon which we rely enable this, promote this and enable us to become better data stewards.

Jax bio dataworldcongress.ngs.20181128finalwithoutbu from Anne Deslattes Mays

]]> 106 2 https://cdn.slidesharecdn.com/ss_thumbnails/jaxbiodataworldcongress-190125162431-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 Wellstein poster embl meeting nov 2018 /adeslat/wellstein-poster-embl-meeting-nov-2018 wellsteinposteremblmeetingnov2018-181129195102
Single molecule real time (SMRT) full length RNA-sequencing reveals novel and distinct mRNA isoforms in human bone marrow cell subpopulations' for the 'EMBL Conference: From Functional Genomics to Systems Biology 2018']]>
Single molecule real time (SMRT) full length RNA-sequencing reveals novel and distinct mRNA isoforms in human bone marrow cell subpopulations' for the 'EMBL Conference: From Functional Genomics to Systems Biology 2018']]> Thu, 29 Nov 2018 19:51:02 GMT /adeslat/wellstein-poster-embl-meeting-nov-2018 adeslat@slideshare.net(adeslat) Wellstein poster embl meeting nov 2018 adeslat Single molecule real time (SMRT) full length RNA-sequencing reveals novel and distinct mRNA isoforms in human bone marrow cell subpopulations' for the 'EMBL Conference: From Functional Genomics to Systems Biology 2018' <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/wellsteinposteremblmeetingnov2018-181129195102-thumbnail.jpg?width=120&height=120&fit=bounds" /> Single molecule real time (SMRT) full length RNA-sequencing reveals novel and distinct mRNA isoforms in human bone marrow cell subpopulations' for the 'EMBL Conference: From Functional Genomics to Systems Biology 2018'

Wellstein poster embl meeting nov 2018 from Anne Deslattes Mays

]]> 61 1 https://cdn.slidesharecdn.com/ss_thumbnails/wellsteinposteremblmeetingnov2018-181129195102-thumbnail.jpg?width=120&height=120&fit=bounds document Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 BioData World Basel 2018 /adeslat/biodata-world-basel-2018 jaxbiodataworldcongress-181129140823
Introduction to Jackson Labs, JMCRS, Clinical Services and Scientific Services at the Jackson Labs. Differences between long and short read sequencing. FAIR Data Action Plan. Metadata needs. Data Commons and the need to capture sample specific gene models discovered.]]>
Introduction to Jackson Labs, JMCRS, Clinical Services and Scientific Services at the Jackson Labs. Differences between long and short read sequencing. FAIR Data Action Plan. Metadata needs. Data Commons and the need to capture sample specific gene models discovered.]]> Thu, 29 Nov 2018 14:08:23 GMT /adeslat/biodata-world-basel-2018 adeslat@slideshare.net(adeslat) BioData World Basel 2018 adeslat Introduction to Jackson Labs, JMCRS, Clinical Services and Scientific Services at the Jackson Labs. Differences between long and short read sequencing. FAIR Data Action Plan. Metadata needs. Data Commons and the need to capture sample specific gene models discovered. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/jaxbiodataworldcongress-181129140823-thumbnail.jpg?width=120&height=120&fit=bounds" /> Introduction to Jackson Labs, JMCRS, Clinical Services and Scientific Services at the Jackson Labs. Differences between long and short read sequencing. FAIR Data Action Plan. Metadata needs. Data Commons and the need to capture sample specific gene models discovered.

BioData World Basel 2018 from Anne Deslattes Mays

]]> 108 3 https://cdn.slidesharecdn.com/ss_thumbnails/jaxbiodataworldcongress-181129140823-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 2014 June 17 PacBio User Group Meeting Presentation "How Looking for a Needle in the Haystack Taught Me to Love the Isoform" /slideshow/june-17-pacbio-user-group-meeting-presentation-how/36293335 anne2014june17pacbiougm-140625093415-phpapp02
Presentation at the PacBio 2014 June 17 User Group Meeting. Isoform discovery with PacBio ICE Software by Elizabeth Tseng. Part of the PacBio SMRTAnalysis 2.2 software for the RS II machine. ICE enables the determination of full length transcripts without assembly. ]]>
Presentation at the PacBio 2014 June 17 User Group Meeting. Isoform discovery with PacBio ICE Software by Elizabeth Tseng. Part of the PacBio SMRTAnalysis 2.2 software for the RS II machine. ICE enables the determination of full length transcripts without assembly. ]]> Wed, 25 Jun 2014 09:34:15 GMT /slideshow/june-17-pacbio-user-group-meeting-presentation-how/36293335 adeslat@slideshare.net(adeslat) 2014 June 17 PacBio User Group Meeting Presentation "How Looking for a Needle in the Haystack Taught Me to Love the Isoform" adeslat Presentation at the PacBio 2014 June 17 User Group Meeting. Isoform discovery with PacBio ICE Software by Elizabeth Tseng. Part of the PacBio SMRTAnalysis 2.2 software for the RS II machine. ICE enables the determination of full length transcripts without assembly. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/anne2014june17pacbiougm-140625093415-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Presentation at the PacBio 2014 June 17 User Group Meeting. Isoform discovery with PacBio ICE Software by Elizabeth Tseng. Part of the PacBio SMRTAnalysis 2.2 software for the RS II machine. ICE enables the determination of full length transcripts without assembly.

2014 June 17 PacBio User Group Meeting Presentation "How Looking for a Needle in the Haystack Taught Me to Love the Isoform" from Anne Deslattes Mays

]]> 2318 5 https://cdn.slidesharecdn.com/ss_thumbnails/anne2014june17pacbiougm-140625093415-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 FGFBP1 pathways control after induction of a conditional transgene in a mouse model: Information derived from mRNA expression pattern analysis /slideshow/lombardi-research-fair2011deslattesmays/32725278 lombardiresearchfair2011deslattesmays-140325141028-phpapp01
A systems biology approach to analyzing large data sets, such as this study which involved five full mouse cDNA arrays allows the researcher to capture a snapshot of the unfolding remodeling events of an organisms response to change, stress or disease. Analyzing data in this form involves filtering the biological signal from the noise. Sorting the noise in appropriate manners is essential to be able to complete the biological story. Building on existing knowledge base, we can complete the picture as long as the proper context of the collection, normalization and analysis is maintained. High throughput technologies such as microarrays and RNA sequencing as enabled by next generation sequencing presents the researcher with the challenge of extracting meaningful information from the measurements. Software tools and analysis techniques are not a substitute to understanding the biological context from which the data are collected. Engineering and digital signal processing has allowed us to derive the understanding of how to reconstruct a signal from the presence of a continual stream of noisy analog data. Sampling frequency and proper filtering are a must to be able to sort out a meaningful signal from the noise. These same principles apply not only to communication theory but also when studying large data such as those that may be collected from high throughput systems such as a Affymetrix mouse cDNA array.]]>
A systems biology approach to analyzing large data sets, such as this study which involved five full mouse cDNA arrays allows the researcher to capture a snapshot of the unfolding remodeling events of an organisms response to change, stress or disease. Analyzing data in this form involves filtering the biological signal from the noise. Sorting the noise in appropriate manners is essential to be able to complete the biological story. Building on existing knowledge base, we can complete the picture as long as the proper context of the collection, normalization and analysis is maintained. High throughput technologies such as microarrays and RNA sequencing as enabled by next generation sequencing presents the researcher with the challenge of extracting meaningful information from the measurements. Software tools and analysis techniques are not a substitute to understanding the biological context from which the data are collected. Engineering and digital signal processing has allowed us to derive the understanding of how to reconstruct a signal from the presence of a continual stream of noisy analog data. Sampling frequency and proper filtering are a must to be able to sort out a meaningful signal from the noise. These same principles apply not only to communication theory but also when studying large data such as those that may be collected from high throughput systems such as a Affymetrix mouse cDNA array.]]> Tue, 25 Mar 2014 14:10:28 GMT /slideshow/lombardi-research-fair2011deslattesmays/32725278 adeslat@slideshare.net(adeslat) FGFBP1 pathways control after induction of a conditional transgene in a mouse model: Information derived from mRNA expression pattern analysis adeslat A systems biology approach to analyzing large data sets, such as this study which involved five full mouse cDNA arrays allows the researcher to capture a snapshot of the unfolding remodeling events of an organisms response to change, stress or disease. Analyzing data in this form involves filtering the biological signal from the noise. Sorting the noise in appropriate manners is essential to be able to complete the biological story. Building on existing knowledge base, we can complete the picture as long as the proper context of the collection, normalization and analysis is maintained. High throughput technologies such as microarrays and RNA sequencing as enabled by next generation sequencing presents the researcher with the challenge of extracting meaningful information from the measurements. Software tools and analysis techniques are not a substitute to understanding the biological context from which the data are collected. Engineering and digital signal processing has allowed us to derive the understanding of how to reconstruct a signal from the presence of a continual stream of noisy analog data. Sampling frequency and proper filtering are a must to be able to sort out a meaningful signal from the noise. These same principles apply not only to communication theory but also when studying large data such as those that may be collected from high throughput systems such as a Affymetrix mouse cDNA array. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/lombardiresearchfair2011deslattesmays-140325141028-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> A systems biology approach to analyzing large data sets, such as this study which involved five full mouse cDNA arrays allows the researcher to capture a snapshot of the unfolding remodeling events of an organisms response to change, stress or disease. Analyzing data in this form involves filtering the biological signal from the noise. Sorting the noise in appropriate manners is essential to be able to complete the biological story. Building on existing knowledge base, we can complete the picture as long as the proper context of the collection, normalization and analysis is maintained. High throughput technologies such as microarrays and RNA sequencing as enabled by next generation sequencing presents the researcher with the challenge of extracting meaningful information from the measurements. Software tools and analysis techniques are not a substitute to understanding the biological context from which the data are collected. Engineering and digital signal processing has allowed us to derive the understanding of how to reconstruct a signal from the presence of a continual stream of noisy analog data. Sampling frequency and proper filtering are a must to be able to sort out a meaningful signal from the noise. These same principles apply not only to communication theory but also when studying large data such as those that may be collected from high throughput systems such as a Affymetrix mouse cDNA array.

FGFBP1 pathways control after induction of a conditional transgene in a mouse model: Information derived from mRNA expression pattern analysis from Anne Deslattes Mays

]]> 342 5 https://cdn.slidesharecdn.com/ss_thumbnails/lombardiresearchfair2011deslattesmays-140325141028-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 RNA Sequencing for Full Length Transcript Discovery /slideshow/rna-sequencing-for-full-length-transcript-discovery/31390221 2014february10-140219092337-phpapp01
Use of second and third generation sequencing technology platforms to create a dataset for the discovery of full length transcripts]]>
Use of second and third generation sequencing technology platforms to create a dataset for the discovery of full length transcripts]]> Wed, 19 Feb 2014 09:23:37 GMT /slideshow/rna-sequencing-for-full-length-transcript-discovery/31390221 adeslat@slideshare.net(adeslat) RNA Sequencing for Full Length Transcript Discovery adeslat Use of second and third generation sequencing technology platforms to create a dataset for the discovery of full length transcripts <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2014february10-140219092337-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Use of second and third generation sequencing technology platforms to create a dataset for the discovery of full length transcripts

RNA Sequencing for Full Length Transcript Discovery from Anne Deslattes Mays

]]> 1847 7 https://cdn.slidesharecdn.com/ss_thumbnails/2014february10-140219092337-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 2013 oct 2 rna sequencing /adeslat/2013-oct-2-rna-sequencing 2013oct2rnasequencing-131002062316-phpapp01
]]>
]]> Wed, 02 Oct 2013 06:23:16 GMT /adeslat/2013-oct-2-rna-sequencing adeslat@slideshare.net(adeslat) 2013 oct 2 rna sequencing adeslat <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2013oct2rnasequencing-131002062316-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" />

2013 oct 2 rna sequencing from Anne Deslattes Mays

]]> 988 2 https://cdn.slidesharecdn.com/ss_thumbnails/2013oct2rnasequencing-131002062316-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 2012 august 16 systems biology rna seq v2 /slideshow/2012-august-16-systems-biology-rna-seq-v2/26176811 2012august16systemsbiologyrnaseqv2-130913140644-phpapp02
]]>
]]> Fri, 13 Sep 2013 14:06:44 GMT /slideshow/2012-august-16-systems-biology-rna-seq-v2/26176811 adeslat@slideshare.net(adeslat) 2012 august 16 systems biology rna seq v2 adeslat <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2012august16systemsbiologyrnaseqv2-130913140644-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" />

2012 august 16 systems biology rna seq v2 from Anne Deslattes Mays

]]> 1673 6 https://cdn.slidesharecdn.com/ss_thumbnails/2012august16systemsbiologyrnaseqv2-130913140644-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 2013 july 25 systems biology rna seq v2 /slideshow/2013-july-25-systems-biology-rna-seq-v2/24648858 2013july25systemsbiologyrnaseqv2-130726070342-phpapp01
]]>
]]> Fri, 26 Jul 2013 07:03:42 GMT /slideshow/2013-july-25-systems-biology-rna-seq-v2/24648858 adeslat@slideshare.net(adeslat) 2013 july 25 systems biology rna seq v2 adeslat <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2013july25systemsbiologyrnaseqv2-130726070342-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" />

2013 july 25 systems biology rna seq v2 from Anne Deslattes Mays

]]> 1014 5 https://cdn.slidesharecdn.com/ss_thumbnails/2013july25systemsbiologyrnaseqv2-130726070342-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 https://cdn.slidesharecdn.com/profile-photo-adeslat-48x48.jpg?cb=1639970358 • Conceived of and created Applied Systems Biology group to establish a scientific research footprint in the US for the Dutch parent company KeyGene. • Conceived, developed and implemented computational methods resulting in three patents for creating more drought tolerant plants (see Patent details below) • Designed and Implemented a hybrid RNASeq processing pipeline in Amazon EC2 instance, utilizing cost benefits of installing tools on T1 micro instances then changing to the larger m2x.4large instance for compute processing. www.sbresearchllc.com https://cdn.slidesharecdn.com/ss_thumbnails/jaxbiodataworldcongress-190125162431-thumbnail.jpg?width=320&height=320&fit=bounds adeslat/jax-bio-dataworldcongressngs20181128finalwithoutbu Jax bio dataworldcongr... https://cdn.slidesharecdn.com/ss_thumbnails/wellsteinposteremblmeetingnov2018-181129195102-thumbnail.jpg?width=320&height=320&fit=bounds adeslat/wellstein-poster-embl-meeting-nov-2018 Wellstein poster embl ... https://cdn.slidesharecdn.com/ss_thumbnails/jaxbiodataworldcongress-181129140823-thumbnail.jpg?width=320&height=320&fit=bounds adeslat/biodata-world-basel-2018 BioData World Basel 2018