Title: Human Genome Analysis
I will discuss various aspects of RNA-seq for human genome analysis, including:
- potential privacy implications
- use of these data for the studying disruption of normal regulation
in cancer with a logic gate model
- use of a state-space model and dimensionality reduction to analyze
time courses
==
i0ngs15
Sunday, October 18, 2015
Saturday, July 11, 2015
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Agencia Universal
Pl. Alqueria Nova 17
Madrid, Spain.
Mr. Benjamin Hook
(Claim Officers)
E-mail: sr_benjamin.hook@consultant.com
Tel: +34 634 031 280
Fax: +34 917 692 656
HOW TO CLAIM YOUR PRIZE !!!
Dear Winner,
This is to notify you that your email address was entered during the Monthly Email Lotto Promo in Conjunction with Euro million Selection draw held on JULY 6TH 2015 and Your Email Address hit the Random selection Number: 8-45-16-31-11, JOKER: 1*9 E-ticket Number: 87698765 And have won the sum of Ђ815,950.00 EUROS (Eight Hundred & Fifteen Thousand Nine Hundred & Fifty Euros) HOW TO CLAIM YOUR PRIZE!!! Simply contact our lottery Agent with the following particulars which are attached to your payment order:
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BATCH NO: EURO/4007/888/116/15.
LUCKY e-TICKET PIN CODE: SBC/40/87698765.
BATCH NO: EURO/4007/888/116/15.
LUCKY e-TICKET PIN CODE: SBC/40/87698765.
And provide him with the following details:
1.Your full name
2.Your direct telephone & fax number
3.Your current Address
4.Occupation
5.Age
6.Nationality
2.Your direct telephone & fax number
3.Your current Address
4.Occupation
5.Age
6.Nationality
Agencia Universal
Pl. Alqueria Nova 17
Madrid, Spain.
Mr. Benjamin Hook
(Claim Officers)
E-mail: sr_benjamin.hook@consultant.com
Tel: +34 634 031 280
Fax: +34 917 692 656
Pl. Alqueria Nova 17
Madrid, Spain.
Mr. Benjamin Hook
(Claim Officers)
E-mail: sr_benjamin.hook@consultant.com
Tel: +34 634 031 280
Fax: +34 917 692 656
Sunday, May 17, 2015
Abstract for seminar at Tel Aviv University
Title: Comparative Genome Analysis
Abstract:
The ENCODE and modENCODE consortia have generated a resource
containing large amounts of transcriptomic data, extensive mapping of
chromatin states, as well as the binding locations of over 300
transcription-regulatory factors for human, worm and fly. The
consortium performed
extensive data integration on this data set. Here
I will give an overview of the data and some of the key analyses.
In particular:
(1) Conservation & Divergence of Transcription
(1a) A novel cross-species clustering algorithm to
integrate the co-expression networks of the three species, resulting in
conserved modules shared between the organisms. These modules are
enriched in developmental genes and exhibited hourglass behavior.
(1b) The extent of the non-coding, non-canonical
transcription is consistent between worm, fly and human.
(1c) In contrast, analyses of pseudogene (fossil genes) show that they
diverged greatly between the organisms, much more so than genes.
Nevertheless, they had a consistent amount of residual transcription.
(2) Conservation of Regulation
(2a) A global optimization algorithm to examine the
hierarchical organization of the regulatory network.
Despite extensive rewiring of binding targets, high-level organization
principles such as a three-layer hierarchy are conserved across the
three species.
(2b) The gene expression levels in the organisms, both coding
and non-coding, can be predicted consistently based on their upstream
histone marks. In fact, a "universal model" with a single set of
cross-organism parameters can predict expression level for both protein
coding genes and ncRNAs.
encodenets.gersteinlab.org
encodeproject.org/comparative
pseudogene.org/psicube
==
i0isgc
Abstract:
The ENCODE and modENCODE consortia have generated a resource
containing large amounts of transcriptomic data, extensive mapping of
chromatin states, as well as the binding locations of over 300
transcription-regulatory factors for human, worm and fly. The
consortium performed
extensive data integration on this data set. Here
I will give an overview of the data and some of the key analyses.
In particular:
(1) Conservation & Divergence of Transcription
(1a) A novel cross-species clustering algorithm to
integrate the co-expression networks of the three species, resulting in
conserved modules shared between the organisms. These modules are
enriched in developmental genes and exhibited hourglass behavior.
(1b) The extent of the non-coding, non-canonical
transcription is consistent between worm, fly and human.
(1c) In contrast, analyses of pseudogene (fossil genes) show that they
diverged greatly between the organisms, much more so than genes.
Nevertheless, they had a consistent amount of residual transcription.
(2) Conservation of Regulation
(2a) A global optimization algorithm to examine the
hierarchical organization of the regulatory network.
Despite extensive rewiring of binding targets, high-level organization
principles such as a three-layer hierarchy are conserved across the
three species.
(2b) The gene expression levels in the organisms, both coding
and non-coding, can be predicted consistently based on their upstream
histone marks. In fact, a "universal model" with a single set of
cross-organism parameters can predict expression level for both protein
coding genes and ncRNAs.
encodenets.gersteinlab.org
encodeproject.org/comparative
pseudogene.org/psicube
==
i0isgc
Wednesday, April 22, 2015
Re: Abstract for Arrowhead's 7th Annual Precision Medicine Conference [i0pgx]
Thanks so much Mark
---
Mollie Roth, J.D.
Managing Partner
PGx Consulting
Tel: 202-280-5887
E-mail: mollie.roth@pgxconsulting.com
www.pgxconsulting.com
Save the Date! Arrowhead's 1st Annual Translational Microbiome Conference, May 14-15, in Boston. For more information about our exciting line-up of speakers, www.microbiomeconference.com
---
Mollie Roth, J.D.
Managing Partner
PGx Consulting
Tel: 202-280-5887
E-mail: mollie.roth@pgxconsulting.com
www.pgxconsulting.com
On Apr 22, 2015, at 6:36 PM, Mark Gerstein <mark@gersteinlab.org> wrote:Genomic Privacy
With every new exciting development in genomics come the often
underappreciated ethical legal and social concerns. Particularly with
regard to issues of privacy, there are ultimate tradeoffs as the
technology continues to develop and the real-life applications of
genomics become more of a reality. Numerous technical solutions have
been proposed, but every technical safeguard is accompanied by
increased complications with analyzing and manipulating datasets.
Moreover, technical solutions invite both white-hat and black-hat
efforts of circumvention, making them less useful in the long-run.
Rather we propose a multi-prong approach to dealing with privacy
issues in genomics that includes technical, regulatory and social
advances that will create an environment that both safeguards privacy,
prevents harms associated with a lack of privacy and promotes
innovation in the fields of genomics and medicine.
Abstract for Arrowhead's 7th Annual Precision Medicine Conference [i0pgx]
Genomic Privacy
With every new exciting development in genomics come the often
underappreciated ethical legal and social concerns. Particularly with
regard to issues of privacy, there are ultimate tradeoffs as the
technology continues to develop and the real-life applications of
genomics become more of a reality. Numerous technical solutions have
been proposed, but every technical safeguard is accompanied by
increased complications with analyzing and manipulating datasets.
Moreover, technical solutions invite both white-hat and black-hat
efforts of circumvention, making them less useful in the long-run.
Rather we propose a multi-prong approach to dealing with privacy
issues in genomics that includes technical, regulatory and social
advances that will create an environment that both safeguards privacy,
prevents harms associated with a lack of privacy and promotes
innovation in the fields of genomics and medicine.
With every new exciting development in genomics come the often
underappreciated ethical legal and social concerns. Particularly with
regard to issues of privacy, there are ultimate tradeoffs as the
technology continues to develop and the real-life applications of
genomics become more of a reality. Numerous technical solutions have
been proposed, but every technical safeguard is accompanied by
increased complications with analyzing and manipulating datasets.
Moreover, technical solutions invite both white-hat and black-hat
efforts of circumvention, making them less useful in the long-run.
Rather we propose a multi-prong approach to dealing with privacy
issues in genomics that includes technical, regulatory and social
advances that will create an environment that both safeguards privacy,
prevents harms associated with a lack of privacy and promotes
innovation in the fields of genomics and medicine.
Fwd: Fw: Invitation to ICEBEM 2015
Title & abstract for
ICEBEM 2015
the 8th International
Conference on Ethics in Biology, Engineering & Medicine (ICEBEM 2015 ) that
will be held at Brooklyn, April 24th to 26th , 2015.
Meeting website:
www.downstate.edu/orthopaedics/bioethics/index.html
Genomic Privacy
With every new exciting development in genomics come the often
underappreciated ethical legal and social concerns. Particularly with
regard to issues of privacy, there are ultimate tradeoffs as the
technology continues to develop and the real-life applications of
genomics become more of a reality. Numerous technical solutions have
been proposed, but every technical safeguard is accompanied by
increased complications with analyzing and manipulating datasets.
Moreover, technical solutions invite both white-hat and black-hat
efforts of circumvention, making them less useful in the long-run.
Rather we propose a multi-prong approach to dealing with privacy
issues in genomics that includes technical, regulatory and social
advances that will create an environment that both safeguards privacy,
prevents harms associated with a lack of privacy and promotes
innovation in the fields of genomics and medicine.
==
i0icebem15
ICEBEM 2015
the 8th International
Conference on Ethics in Biology, Engineering & Medicine (ICEBEM 2015 ) that
will be held at Brooklyn, April 24th to 26th , 2015.
Meeting website:
www.downstate.edu/orthopaedics/bioethics/index.html
Genomic Privacy
With every new exciting development in genomics come the often
underappreciated ethical legal and social concerns. Particularly with
regard to issues of privacy, there are ultimate tradeoffs as the
technology continues to develop and the real-life applications of
genomics become more of a reality. Numerous technical solutions have
been proposed, but every technical safeguard is accompanied by
increased complications with analyzing and manipulating datasets.
Moreover, technical solutions invite both white-hat and black-hat
efforts of circumvention, making them less useful in the long-run.
Rather we propose a multi-prong approach to dealing with privacy
issues in genomics that includes technical, regulatory and social
advances that will create an environment that both safeguards privacy,
prevents harms associated with a lack of privacy and promotes
innovation in the fields of genomics and medicine.
==
i0icebem15
Sunday, April 19, 2015
Abstract for Talk at BioIT World 2015
Human Genome Analysis
Identification of noncoding cancer "drivers" from thousands of somatic
alterations is an unsolved problem. Here, we developed a computational
framework to annotate cancer regulatory mutations. The framework
combines an adjustable data context summarizing large-scale genomics
and cancer-relevant datasets with an efficient variant prioritization
pipeline. To prioritize high impact variants, we developed a weighted
scoring scheme to score each mutation's impact.
Session in
http://www.bio-itworldexpo.com/Clinical-Omics/
Podcast
http://www.bio-itworldexpo.com/Bio-It_Expo_Content.aspx?id=146139
Identification of noncoding cancer "drivers" from thousands of somatic
alterations is an unsolved problem. Here, we developed a computational
framework to annotate cancer regulatory mutations. The framework
combines an adjustable data context summarizing large-scale genomics
and cancer-relevant datasets with an efficient variant prioritization
pipeline. To prioritize high impact variants, we developed a weighted
scoring scheme to score each mutation's impact.
Session in
http://www.bio-itworldexpo.com/Clinical-Omics/
Podcast
http://www.bio-itworldexpo.com/Bio-It_Expo_Content.aspx?id=146139
Sunday, April 5, 2015
Fwd: Abstract for Structural Genomics Conference in Israel
Abstract for "ISCG2015: Deep Sequencing Meets Structural Biology,"
Weizmann Institute, on June 7th-11th, 2015
Title: Analysis of Protein Networks
Protein-protein interaction (PPI) networks may be studied through the
lens of both 3-dimensional protein structures as well as the
large-scale genome variation data being generated as part of
next-generation sequencing initiatives. In terms of protein structural
data, I will describe how mapping the structures of protein complexes
onto PPI networks enables the classification of hubs into two distinct
types: multi- and singlish-interface. These two categories exhibit
very distinct properties, especially in terms of the well-known
preferential attachment model of network growth. Secondly, I will
discuss how the integration of alternative conformations with PPI
networks further highlights interesting disparities, with the
permanent multi-interface hubs tending to exhibit a greater degree of
conformational plasticity relative to singlish-interface hubs. In
addition, I will briefly discuss how alternative conformations are
being culled from the PDB to study the significance of sequence
variation in the context of allosteric behavior. I will then discuss
the some of the insights gained by integrating variation data with
these networks (especially when using population-scale sequencing data
from the 1000 Genomes Project). Several well-known results are
recapitulated using this data: greater network centralityis associated
with a greater degree of negative selection, and the proclivity of the
network tends to be under positive selection. Finally, I will show how
this type of data further illuminates aspects of the intricacies of
protein structures and motions.
Integration of protein motions with molecular networks reveals
different mechanisms for permanent and transient interactions.
N Bhardwaj, A Abyzov, D Clarke, C Shou, MB Gerstein (2011). Protein
Sci 20:1745-54.
Integrative annotation of variants from 1092 humans: application to
cancer genomics.
E Khurana, Y Fu, V Colonna, XJ Mu, HM Kang, T Lappalainen, A Sboner, L
Lochovsky, J Chen, A Harmanci, J Das, A Abyzov, S Balasubramanian, K
Beal, D Chakravarty, D Challis, Y Chen, D Clarke, L Clarke, F
Cunningham, US Evani, P Flicek, R Fragoza, E Garrison, R Gibbs, ZH
Gumus, J Herrero, N Kitabayashi, Y Kong, K Lage, V Liluashvili, SM
Lipkin, DG MacArthur, G Marth, D Muzny, TH Pers, GR Ritchie, JA
Rosenfeld, C Sisu, X Wei, M Wilson, Y Xue, F Yu, 1000 Genomes Project
Consortium, ET Dermitzakis, H Yu, MA Rubin, C Tyler-Smith, M Gerstein
(2013). Science 342: 1235587
==
ID=i0isgc
Weizmann Institute, on June 7th-11th, 2015
Title: Analysis of Protein Networks
Protein-protein interaction (PPI) networks may be studied through the
lens of both 3-dimensional protein structures as well as the
large-scale genome variation data being generated as part of
next-generation sequencing initiatives. In terms of protein structural
data, I will describe how mapping the structures of protein complexes
onto PPI networks enables the classification of hubs into two distinct
types: multi- and singlish-interface. These two categories exhibit
very distinct properties, especially in terms of the well-known
preferential attachment model of network growth. Secondly, I will
discuss how the integration of alternative conformations with PPI
networks further highlights interesting disparities, with the
permanent multi-interface hubs tending to exhibit a greater degree of
conformational plasticity relative to singlish-interface hubs. In
addition, I will briefly discuss how alternative conformations are
being culled from the PDB to study the significance of sequence
variation in the context of allosteric behavior. I will then discuss
the some of the insights gained by integrating variation data with
these networks (especially when using population-scale sequencing data
from the 1000 Genomes Project). Several well-known results are
recapitulated using this data: greater network centralityis associated
with a greater degree of negative selection, and the proclivity of the
network tends to be under positive selection. Finally, I will show how
this type of data further illuminates aspects of the intricacies of
protein structures and motions.
Integration of protein motions with molecular networks reveals
different mechanisms for permanent and transient interactions.
N Bhardwaj, A Abyzov, D Clarke, C Shou, MB Gerstein (2011). Protein
Sci 20:1745-54.
Integrative annotation of variants from 1092 humans: application to
cancer genomics.
E Khurana, Y Fu, V Colonna, XJ Mu, HM Kang, T Lappalainen, A Sboner, L
Lochovsky, J Chen, A Harmanci, J Das, A Abyzov, S Balasubramanian, K
Beal, D Chakravarty, D Challis, Y Chen, D Clarke, L Clarke, F
Cunningham, US Evani, P Flicek, R Fragoza, E Garrison, R Gibbs, ZH
Gumus, J Herrero, N Kitabayashi, Y Kong, K Lage, V Liluashvili, SM
Lipkin, DG MacArthur, G Marth, D Muzny, TH Pers, GR Ritchie, JA
Rosenfeld, C Sisu, X Wei, M Wilson, Y Xue, F Yu, 1000 Genomes Project
Consortium, ET Dermitzakis, H Yu, MA Rubin, C Tyler-Smith, M Gerstein
(2013). Science 342: 1235587
==
ID=i0isgc
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