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Χωρίς Τίτλο!
Manolis Kellis, Ph.D.
Professor, MIT Computer Science and Artificial Intelligence Lab
Member, Broad Institute of MIT and Harvard
Date: Monday, October 4th, 2021, 19:00GR
zoom: =
<https://l.facebook.com/l.php?u=3Dhttps%3A%2F%2Fzoom.us%2Fj%2F97078540320=
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=20
Abstract: Disease-associated variants lie primarily in non-coding =
regions, increasing the urgency of understanding how gene-regulatory =
circuitry impacts human disease. To address this challenge, we generate =
comparative genomics, epigenomic, and transcriptional maps, spanning 823 =
human tissues, 1500 individuals, and 20 million single cells. We link =
variants to target genes, upstream regulators, cell types of action, and =
perturbed pathways, and predict causal genes and regions to provide =
unbiased views of disease mechanisms, sometimes re-shaping our =
understanding. We find that Alzheimer=E2=80=99s variants act primarily =
through immune processes, rather than neuronal processes, and the =
strongest genetic association with obesity acts via energy =
storage/dissipation rather than appetite/exercise decisions. We combine =
single-cell profiles, tissue-level variation, and genetic variation =
across healthy and diseased individuals to map genetic effects into =
epigenomic, transcriptional, and function changes at single-cell =
resolution, to recognize cell-type-specific disease-associated somatic =
mutations indicative of mosaicism, and to recognize multi-tissue =
single-cell effects of exercise and obesity. We expand these methods to =
electronic health records to recognize multi-phenotype effects of =
genetics, environment, and disease, combining clinical notes, lab tests, =
and diverse data modalities despite missing data. We integrate large =
cohorts to factorize phenotype-genotype correlations to reveal distinct =
biological contributors of complex diseases and traits, to partition =
disease complexity, and to stratify patients for pathway-matched =
treatments. Lastly, we develop massively-parallel, programmable and =
modular technologies for manipulating these pathways by high-throughput =
reporter assays, genome editing, and gene targeting in human cells and =
mice, to propose new therapeutic hypotheses in Alzheimer=E2=80=99s, =
obesity, and cancer. These results provide a roadmap for translating =
genetic findings into mechanistic insights and ultimately new =
therapeutic avenues for complex disease and cancer.=20
Bio: Manolis Kellis is a professor of computer science at MIT, a member =
of the Broad Institute of MIT and Harvard, a principal investigator of =
the Computer Science and Artificial Intelligence Lab at MIT, and head of =
the MIT Computational Biology Group (compbio.mit.edu). His research =
includes disease circuitry, genetics, genomics, epigenomics, coding =
genes, non-coding RNAs, regulatory genomics, and comparative genomics, =
applied to Alzheimer's Disease, Obesity, Schizophrenia, Cardiac =
Disorders, Cancer, and Immune Disorders, and multiple other disorders. =
He has led several large-scale genomics projects, including the Roadmap =
Epigenomics project, the ENCODE project, the Genotype Tissue-Expression =
(GTEx) project, and comparative genomics projects in mammals, flies, and =
yeasts. He received the US Presidential Early Career Award in Science =
and Engineering (PECASE) by US President Barack Obama, the Mendel Medal =
for Outstanding Achievements in Science, the NSF CAREER award, the =
Alfred P. Sloan Fellowship, the Technology Review TR35 recognition, the =
AIT Niki Award, and the Sprowls award for the best Ph.D. thesis in =
computer science at MIT. He has authored over 240 journal publications =
cited more than 120,000 times. He has obtained more than 20 multi-year =
grants from the NIH, and his trainees hold faculty positions at =
Stanford, Harvard, CMU, McGill, Johns Hopkins, UCLA, and other top =
universities. He lived in Greece and France before moving to the US, and =
he studied and conducted research at MIT, the Xerox Palo Alto Research =
Center, and the Cold Spring Harbor Lab. For more info, see: =
<http://compbio.mit.edu> compbio.mit.edu
=20
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class=3DWordSection1><p class=3DMsoNormal><span =
lang=3DEL>=CE=98=CE=95=CE=9C=CE=91</span>: From genomics to =
therapeutics: Single-cell dissection and manipulation of disease =
circuitry, Manolis Kellis, Ph.D. (<span =
lang=3DEL>=CE=9C=CE=99=CE=A4</span>)<o:p></o:p></p><p =
class=3DMsoNormal><span =
lang=3DEL>=CE=91=CE=A0=CE=9F=CE=A3=CE=A4=CE=9F=CE=9B=CE=95=CE=91=CE=A3</s=
pan>: Rena Kalaitzaki <rena@xxxxxxxxxx><o:p></o:p></p><p =
class=3DMsoNormal><o:p> </o:p></p><p><o:p> </o:p></p><p><span =
lang=3DEL>=CE=A4=CE=B7 <b>=CE=94=CE=B5=CF=85=CF=84=CE=AD=CF=81=CE=B1, 4 =
=CE=9F=CE=BA=CF=84=CF=89=CE=B2=CF=81=CE=AF=CE=BF=CF=85, 2021, =
</b>=CF=83=CF=84=CE=B9=CF=82 <b>19.00</b></span><b>GR</b><span =
lang=3DEL>, =CE=BF =
=CE=BA=CE=B1=CE=B8=CE=B7=CE=B3=CE=B7=CF=84=CE=AE=CF=82 =
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=CF=84=CE=BC=CE=AE=CE=BC=CE=B1=CF=84=CE=BF=CF=82 =
=CE=95=CF=80=CE=B9=CF=83=CF=84=CE=AE=CE=BC=CE=B7=CF=82 =
=CE=A5=CF=80=CE=BF=CE=BB=CE=BF=CE=B3=CE=B9=CF=83=CF=84=CF=8E=CE=BD =
=CF=84=CE=BF=CF=85 =
=CE=A0=CE=B1=CE=BD=CE=B5=CF=80=CE=B9=CF=83=CF=84=CE=B7=CE=BC=CE=AF=CE=BF=CF=
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=CF=84=CF=89=CE=BD =
=CE=94=CE=B1=CF=81=CE=B2=CE=B9=CE=BD=CE=B9=CE=BA=CF=8E=CE=BD =
=CE=94=CE=B5=CF=85=CF=84=CE=AD=CF=81=CF=89=CE=BD. </span>=CE=97 =
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=CE=BA=CE=B1=CE=B9 =CF=84=CE=BF =
=CF=83=CF=8D=CE=BD=CF=84=CE=BF=CE=BC=CE=BF =
=CE=B2=CE=B9=CE=BF=CE=B3=CF=81=CE=B1=CF=86=CE=B9=CE=BA=CF=8C =
=CF=84=CE=BF=CF=85 =CE=BA=CE=B1=CE=B8=CE=B7=CE=B3=CE=B7=CF=84=CE=AE =
=CE=9C=CE=B1=CE=BD=CF=8C=CE=BB=CE=B7 =
=CE=9A=CE=AD=CE=BB=CE=BB=CE=B7.<o:p></o:p></p><div><p =
class=3DMsoNormal> =
<o:p></o:p></p><div><p><o:p> </o:p></p><div><div><p =
class=3DMsoNormal align=3Dcenter =
style=3D'mso-margin-top-alt:0cm;margin-right:0cm;margin-bottom:5.0pt;marg=
in-left:36.0pt;text-align:center;text-indent:-18.0pt'><b><span =
style=3D'font-size:14.0pt;font-family:"Arial",sans-serif'>From genomics =
to therapeutics: <br>Single-cell dissection and manipulation of disease =
circuitry</span></b><o:p></o:p></p><p class=3DMsoNormal align=3Dcenter =
style=3D'mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;margin-left:1=
8.0pt;text-align:center'><b><span =
style=3D'font-size:12.0pt;font-family:"Arial",sans-serif'>Manolis =
Kellis, Ph.D.</span></b><span =
style=3D'font-size:12.0pt;font-family:"Arial",sans-serif'><br></span><spa=
n style=3D'font-family:"Arial",sans-serif'>Professor, MIT Computer =
Science and Artificial Intelligence Lab<br>Member, Broad Institute of =
MIT and Harvard</span><o:p></o:p></p><p class=3DMsoNormal align=3Dcenter =
style=3D'mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;margin-left:1=
8.0pt;text-align:center'><span =
style=3D'font-family:"Arial",sans-serif'>Date: Monday, October 4th, =
2021, 19:00GR</span><o:p></o:p></p><p class=3DMsoNormal align=3Dcenter =
style=3D'mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;margin-left:1=
8.0pt;text-align:center'><span =
style=3D'font-family:"Arial",sans-serif'>zoom</span><span =
style=3D'font-size:11.5pt;font-family:"Segoe UI =
Historic",sans-serif;color:#050505;background:white'>: <a =
href=3D"https://l.facebook.com/l.php?u=3Dhttps%3A%2F%2Fzoom.us%2Fj%2F9707=
8540320%3Ffbclid%3DIwAR2ZU99ULod-pmYbdJkNl3ADD-2DGiySVSKHqWHMp99SCj_wNgIZ=
CWhbFpU&h=3DAT0ZHQyOC9RPB7HYuleoW_8zldHnnGI71KJ7iewnfB8Wzn3hdbiFdLdN5=
0vWUZHCD1kym5fxm2QaE1MkHOjZ6zGBd495nquNnrITqwTtaqwl6ydAXEuGqHxW-HJCb6Y-&a=
mp;__tn__=3D-UK-R&c%5b0%5d=3DAT2mUFzt9_8Oqqy5TNP7Cssj868OTlKB7W8iw15W=
6XfwFRyf26c8EUvBnHyJfeyreepxCDrOE2TNdPME-kdfQeS4DEijv6b7LNcUtXDECeUXOQwxq=
xBdbG6mQgkGdbDRGFlybZ6jUbBTVmuJZ4vzc77U3os" target=3D"_blank"><span =
style=3D'font-family:"inherit",serif;border:none windowtext =
1.0pt;padding:0cm'>https://zoom.us/j/97078540320</span></a></span><span =
style=3D'font-family:"Arial",sans-serif'> =
</span><o:p></o:p></p><p class=3DMsoNormal align=3Dcenter =
style=3D'mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;margin-left:1=
8.0pt;text-align:center'><o:p> </o:p></p><p class=3DMsoNormal =
style=3D'mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;margin-left:1=
8.0pt'><span style=3D'font-family:"Arial",sans-serif'>Abstract: =
Disease-associated variants lie primarily in non-coding regions, =
increasing the urgency of understanding how gene-regulatory circuitry =
impacts human disease. To address this challenge, we generate =
comparative genomics, epigenomic, and transcriptional maps, spanning 823 =
human tissues, 1500 individuals, and 20 million single cells. We link =
variants to target genes, upstream regulators, cell types of action, and =
perturbed pathways, and predict causal genes and regions to provide =
unbiased views of disease mechanisms, sometimes re-shaping our =
understanding. We find that Alzheimer=E2=80=99s variants act primarily =
through immune processes, rather than neuronal processes, and the =
strongest genetic association with obesity acts via energy =
storage/dissipation rather than appetite/exercise decisions. We combine =
single-cell profiles, tissue-level variation, and genetic variation =
across healthy and diseased individuals to map genetic effects into =
epigenomic, transcriptional, and function changes at single-cell =
resolution, to recognize cell-type-specific disease-associated somatic =
mutations indicative of mosaicism, and to recognize multi-tissue =
single-cell effects of exercise and obesity. We expand these methods to =
electronic health records to recognize multi-phenotype effects of =
genetics, environment, and disease, combining clinical notes, lab tests, =
and diverse data modalities despite missing data. We integrate large =
cohorts to factorize phenotype-genotype correlations to reveal distinct =
biological contributors of complex diseases and traits, to partition =
disease complexity, and to stratify patients for pathway-matched =
treatments. Lastly, we develop massively-parallel, programmable and =
modular technologies for manipulating these pathways by high-throughput =
reporter assays, genome editing, and gene targeting in human cells and =
mice, to propose new therapeutic hypotheses in Alzheimer=E2=80=99s, =
obesity, and cancer. These results provide a roadmap for translating =
genetic findings into mechanistic insights and ultimately new =
therapeutic avenues for complex disease and cancer. =
</span><o:p></o:p></p><p class=3DMsoNormal =
style=3D'margin-left:18.0pt'><span =
style=3D'font-family:"Arial",sans-serif'>Bio:<b> Manolis Kellis</b> is a =
professor of computer science at MIT, a member of the Broad Institute of =
MIT and Harvard, a principal investigator of the Computer Science and =
Artificial Intelligence Lab at MIT, and head of the MIT Computational =
Biology Group (compbio.mit.edu). His research includes disease =
circuitry, genetics, genomics, epigenomics, coding genes, non-coding =
RNAs, regulatory genomics, and comparative genomics, applied to =
Alzheimer's Disease, Obesity, Schizophrenia, Cardiac Disorders, Cancer, =
and Immune Disorders, and multiple other disorders. He has led several =
large-scale genomics projects, including the Roadmap Epigenomics =
project, the ENCODE project, the Genotype Tissue-Expression (GTEx) =
project, and comparative genomics projects in mammals, flies, and =
yeasts. He received the US Presidential Early Career Award in Science =
and Engineering (PECASE) by US President Barack Obama, the Mendel Medal =
for Outstanding Achievements in Science, the NSF CAREER award, the =
Alfred P. Sloan Fellowship, the Technology Review TR35 recognition, the =
AIT Niki Award, and the Sprowls award for the best Ph.D. thesis in =
computer science at MIT. He has authored over 240 journal publications =
cited more than 120,000 times. He has obtained more than 20 multi-year =
grants from the NIH, and his trainees hold faculty positions at =
Stanford, Harvard, CMU, McGill, Johns Hopkins, UCLA, and other top =
universities. He lived in Greece and France before moving to the US, and =
he studied and conducted research at MIT, the Xerox Palo Alto Research =
Center, and the Cold Spring Harbor Lab. For more info, see: </span><a =
href=3D"http://compbio.mit.edu";><span =
style=3D'font-family:"Arial",sans-serif;color:#034990'>compbio.mit.edu</s=
pan></a><o:p></o:p></p><p class=3DMsoNormal =
style=3D'margin-left:18.0pt'><span =
style=3D'font-family:"Arial",sans-serif'> </span><o:p></o:p></p></di=
v></div></div></div></div></body></html>
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ΛΙΣΤΑ ΚΟΙΝΟΠΟΙΗΣΕΩΝ ΣΤΗ ΦΙΛΟΣΟΦΙΚΗ ΣΧΟΛΗ.