Geoff Varner free skate from 2006 NHK Trophy in Japan
published: 04 Dec 2006
Geoffry Varner-2006 Nationals - Junior Men Short Program
Geoffry Varner - 2006 US Nationals - Junior men - Short Program.
1st place.
Technical elements - 30.29
Program components-27.29
Total-57.58
published: 30 Nov 2010
Sisters4fitness Dr Geoffrey Varner, Home Alive: 11 Must Rules for Surviving Encounters w/ Police
Stephanie Gaines-Bryant w/Dr. Geoffrey Mount Varner about his book "Home Alive: 11 Must Rules for Surviving Encounters w/Police". Talks about how to deal with a police stop and walk away alive.
published: 29 Jun 2017
COVID-19 Vaccine Interview ft. Dr. Geoffrey Varner
Interview time stamps and summary:
https://docs.google.com/document/d/1jUTBe1bQ1yeN16CGId7UarFsTVxrJvamKC0Hx9Oqg8A/edit?usp=sharing
published: 21 May 2021
BSTModelKit.jl Building Biochemical Systems Theory Models | Jeffrey Varner | JuliaCon 2023
In this talk, we introduce the BSTModelKit.jl package, which enables the construction and analysis of biochemical systems theory (BST) models of metabolic and single transduction networks. We demonstrate the capabilities of BSTModelKit.jl by analyzing the thrombin generation dynamics of a population of synthetic patients before and during pregnancy developed from an ongoing study at the University of Vermont supported by the National Institute of Health (NIH).
Biochemical systems theory (BST), developed beginning in the 1960s by Savageau, Voit, and others, is a modeling framework based on ordinary differential equations (ODE) in which biochemical processes are represented using power-law expansions in the system's variables. In this talk, we introduce BSTModelKit.jl, a Julia package dedic...
published: 11 Sep 2023
Systems Conversations 10/27/2017 - Jeffrey Varner
Jeffrey Varner is a Professor in the Robert Frederick Smith School of Chemical and Biomolecular Engineering at Cornell University. Jeffrey Varner holds a Ph.D degree in Chemical Engineering from Purdue University where he explored modeling and analysis of metabolic networks in the lab of Prof. Ramkrishna. After a postdoc in the Department of Biology at the ETH-Zurich under the direction of Jay Bailey and a research position at Genencor-DuPont, Palo Alto, CA, Prof. Varner joined the faculty of the Chemical and Biomolecular Engineering department at Cornell University as an Assistant Professor in 2006. In the fall of 2011, Prof. Varner was promoted to Associate Professor with tenure, and in 2016 to the rank of Professor. The Varnerlab is interested in modeling and analysis of signal transduc...
published: 07 Nov 2017
Geoffrey Varner Speech w new intro
published: 29 Jun 2019
Survivor - Jeff Varner OUTS Zeke Smith as TRANSGENDER!!
I'm sure Jeff is horribly embarrassed about outing this to the world...which is funny because people thought he was GAY when he first appeared on Survivor Australia.
But it's good to see the other tribemates back Zeke up
published: 13 Apr 2017
Sisters4Fitness, Dr. Geoffrey Mount Varner, Vaccine Season.mp4 1
Stephanie Gaines-Bryant sits down with Dr. Geoffrey Mount Varner to discuss flu and COVID season this Fall 2023.
published: 10 Oct 2023
Jeff Varner Being a Pick Me Gay 🌈
I have a new channel that you can find here: https://www.youtube.com/channel/UCATrdOWnIsWQIHe1F3_EBhQ
Click https://www.patreon.com/EagerTurtle if you would like to consider joining my Patreon for either $1 (The Neat Lady), $3 (The Dragon Slayer), or $5 (The Golden God).
Stephanie Gaines-Bryant w/Dr. Geoffrey Mount Varner about his book "Home Alive: 11 Must Rules for Surviving Encounters w/Police". Talks about how to deal with ...
Stephanie Gaines-Bryant w/Dr. Geoffrey Mount Varner about his book "Home Alive: 11 Must Rules for Surviving Encounters w/Police". Talks about how to deal with a police stop and walk away alive.
Stephanie Gaines-Bryant w/Dr. Geoffrey Mount Varner about his book "Home Alive: 11 Must Rules for Surviving Encounters w/Police". Talks about how to deal with a police stop and walk away alive.
In this talk, we introduce the BSTModelKit.jl package, which enables the construction and analysis of biochemical systems theory (BST) models of metabolic and s...
In this talk, we introduce the BSTModelKit.jl package, which enables the construction and analysis of biochemical systems theory (BST) models of metabolic and single transduction networks. We demonstrate the capabilities of BSTModelKit.jl by analyzing the thrombin generation dynamics of a population of synthetic patients before and during pregnancy developed from an ongoing study at the University of Vermont supported by the National Institute of Health (NIH).
Biochemical systems theory (BST), developed beginning in the 1960s by Savageau, Voit, and others, is a modeling framework based on ordinary differential equations (ODE) in which biochemical processes are represented using power-law expansions in the system's variables. In this talk, we introduce BSTModelKit.jl, a Julia package dedicated to the automatic generation and analysis of BST models of metabolic and signal transduction networks. BSTModelKit.jl features a simple domain-specific language (DSL) that specifies the model reaction network, methods to estimate steady-state and dynamic solutions to BST models, and methods to conduct global sensitivity analysis of BST model parameters.
We construct and analyze BST models of the thrombin generation dynamics of synthetic patients before and during pregnancy to demonstrate the features of the BSTModelKit.jl package. Women are at higher risk for a blood clot during pregnancy, childbirth, and up to 3 months after delivering a baby. The Centers for Disease Control and Prevention estimates that pregnant women are up to 5 times more likely to experience a blood clot than women who are not pregnant. A synthetic population of pregnant women was developed from patient data to understand better this increased clotting risk. Measurements of 11 coagulation factors involved with the regulation of thrombin generation and measurements of the hormones Estradiol and Progesterone were collected longitudinally from N = 38 women at three visits: V1 non-pregnant, V2 first trimester, and V3 third trimester. A corresponding Thrombin Generation Assay (TGA) was conducted for each patient sample, and parameters describing the dynamics were extracted.
A joint probability model (assumed to be a multivariate normal distribution) was constructed from this matched data by computing the mean vector and covariance arrays from the experimental measurements. The probability model was then used to generate synthetic patient populations (dimension 1k, 10k, and 100k patients) that could be used in subsequent Machine Learning (ML) studies. One such ML study gauged how representative the synthetic population was of the original data. Next, an ordinary differential equation BST model of coagulation dynamics in individual patients was developed from the synthetic population and used to predict the patient TGA parameters. Patient-specific BST model parameters were estimated and used to simulate TGA patient data; the synthetic-patient BST models were consistent with true-patient TGA measurements. Further, global sensitivity analysis of the BST models identified which model parameters controlled the different aspects of the TGA measurements. Finally, by clustering the synthetic and actual patient data, using a radial basis function distance metric, our synthetic population recapitulated the empirically measured differences between the non-pregnant and pregnant states.
The following grants supported this work: The Interaction of Basal Risk, Pharmacological Ovulation Induction, Pregnancy and Delivery on Hemostatic Balance NIH NHLBI R-33 HL 141787 (PI’s Bernstein, Orfeo) and the Pregnancy Phenotype and Predisposition to Preeclampsia NIH NHLBI R01 HL 71944 (PI Bernstein).
Time Stamps:
00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/JuliaCommunity/YouTubeVideoTimestamps
Interested in improving the auto generated captions? Get involved here: https://github.com/JuliaCommunity/YouTubeVideoSubtitles
In this talk, we introduce the BSTModelKit.jl package, which enables the construction and analysis of biochemical systems theory (BST) models of metabolic and single transduction networks. We demonstrate the capabilities of BSTModelKit.jl by analyzing the thrombin generation dynamics of a population of synthetic patients before and during pregnancy developed from an ongoing study at the University of Vermont supported by the National Institute of Health (NIH).
Biochemical systems theory (BST), developed beginning in the 1960s by Savageau, Voit, and others, is a modeling framework based on ordinary differential equations (ODE) in which biochemical processes are represented using power-law expansions in the system's variables. In this talk, we introduce BSTModelKit.jl, a Julia package dedicated to the automatic generation and analysis of BST models of metabolic and signal transduction networks. BSTModelKit.jl features a simple domain-specific language (DSL) that specifies the model reaction network, methods to estimate steady-state and dynamic solutions to BST models, and methods to conduct global sensitivity analysis of BST model parameters.
We construct and analyze BST models of the thrombin generation dynamics of synthetic patients before and during pregnancy to demonstrate the features of the BSTModelKit.jl package. Women are at higher risk for a blood clot during pregnancy, childbirth, and up to 3 months after delivering a baby. The Centers for Disease Control and Prevention estimates that pregnant women are up to 5 times more likely to experience a blood clot than women who are not pregnant. A synthetic population of pregnant women was developed from patient data to understand better this increased clotting risk. Measurements of 11 coagulation factors involved with the regulation of thrombin generation and measurements of the hormones Estradiol and Progesterone were collected longitudinally from N = 38 women at three visits: V1 non-pregnant, V2 first trimester, and V3 third trimester. A corresponding Thrombin Generation Assay (TGA) was conducted for each patient sample, and parameters describing the dynamics were extracted.
A joint probability model (assumed to be a multivariate normal distribution) was constructed from this matched data by computing the mean vector and covariance arrays from the experimental measurements. The probability model was then used to generate synthetic patient populations (dimension 1k, 10k, and 100k patients) that could be used in subsequent Machine Learning (ML) studies. One such ML study gauged how representative the synthetic population was of the original data. Next, an ordinary differential equation BST model of coagulation dynamics in individual patients was developed from the synthetic population and used to predict the patient TGA parameters. Patient-specific BST model parameters were estimated and used to simulate TGA patient data; the synthetic-patient BST models were consistent with true-patient TGA measurements. Further, global sensitivity analysis of the BST models identified which model parameters controlled the different aspects of the TGA measurements. Finally, by clustering the synthetic and actual patient data, using a radial basis function distance metric, our synthetic population recapitulated the empirically measured differences between the non-pregnant and pregnant states.
The following grants supported this work: The Interaction of Basal Risk, Pharmacological Ovulation Induction, Pregnancy and Delivery on Hemostatic Balance NIH NHLBI R-33 HL 141787 (PI’s Bernstein, Orfeo) and the Pregnancy Phenotype and Predisposition to Preeclampsia NIH NHLBI R01 HL 71944 (PI Bernstein).
Time Stamps:
00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/JuliaCommunity/YouTubeVideoTimestamps
Interested in improving the auto generated captions? Get involved here: https://github.com/JuliaCommunity/YouTubeVideoSubtitles
Jeffrey Varner is a Professor in the Robert Frederick Smith School of Chemical and Biomolecular Engineering at Cornell University. Jeffrey Varner holds a Ph.D d...
Jeffrey Varner is a Professor in the Robert Frederick Smith School of Chemical and Biomolecular Engineering at Cornell University. Jeffrey Varner holds a Ph.D degree in Chemical Engineering from Purdue University where he explored modeling and analysis of metabolic networks in the lab of Prof. Ramkrishna. After a postdoc in the Department of Biology at the ETH-Zurich under the direction of Jay Bailey and a research position at Genencor-DuPont, Palo Alto, CA, Prof. Varner joined the faculty of the Chemical and Biomolecular Engineering department at Cornell University as an Assistant Professor in 2006. In the fall of 2011, Prof. Varner was promoted to Associate Professor with tenure, and in 2016 to the rank of Professor. The Varnerlab is interested in modeling and analysis of signal transduction and metabolic networks using kinetic and constraints based modeling techniques. We are also interested in automatic code generation, and model identification using multi-objective optimization. Prof. Varner has received several awards, including an NSF Career Award, and the College of Engineering Teaching Award.
Watch his Systems Seminar talk, 'Mathematical Modeling and Analysis of Metabolic and Information Processing Systems in Biology' here: https://cornell.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=f66a0982-a6df-414a-9d63-4b6e2fa5987b
Jeffrey Varner is a Professor in the Robert Frederick Smith School of Chemical and Biomolecular Engineering at Cornell University. Jeffrey Varner holds a Ph.D degree in Chemical Engineering from Purdue University where he explored modeling and analysis of metabolic networks in the lab of Prof. Ramkrishna. After a postdoc in the Department of Biology at the ETH-Zurich under the direction of Jay Bailey and a research position at Genencor-DuPont, Palo Alto, CA, Prof. Varner joined the faculty of the Chemical and Biomolecular Engineering department at Cornell University as an Assistant Professor in 2006. In the fall of 2011, Prof. Varner was promoted to Associate Professor with tenure, and in 2016 to the rank of Professor. The Varnerlab is interested in modeling and analysis of signal transduction and metabolic networks using kinetic and constraints based modeling techniques. We are also interested in automatic code generation, and model identification using multi-objective optimization. Prof. Varner has received several awards, including an NSF Career Award, and the College of Engineering Teaching Award.
Watch his Systems Seminar talk, 'Mathematical Modeling and Analysis of Metabolic and Information Processing Systems in Biology' here: https://cornell.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=f66a0982-a6df-414a-9d63-4b6e2fa5987b
I'm sure Jeff is horribly embarrassed about outing this to the world...which is funny because people thought he was GAY when he first appeared on Survivor Austr...
I'm sure Jeff is horribly embarrassed about outing this to the world...which is funny because people thought he was GAY when he first appeared on Survivor Australia.
But it's good to see the other tribemates back Zeke up
I'm sure Jeff is horribly embarrassed about outing this to the world...which is funny because people thought he was GAY when he first appeared on Survivor Australia.
But it's good to see the other tribemates back Zeke up
I have a new channel that you can find here: https://www.youtube.com/channel/UCATrdOWnIsWQIHe1F3_EBhQ
Click https://www.patreon.com/EagerTurtle if you would li...
I have a new channel that you can find here: https://www.youtube.com/channel/UCATrdOWnIsWQIHe1F3_EBhQ
Click https://www.patreon.com/EagerTurtle if you would like to consider joining my Patreon for either $1 (The Neat Lady), $3 (The Dragon Slayer), or $5 (The Golden God).
I have a new channel that you can find here: https://www.youtube.com/channel/UCATrdOWnIsWQIHe1F3_EBhQ
Click https://www.patreon.com/EagerTurtle if you would like to consider joining my Patreon for either $1 (The Neat Lady), $3 (The Dragon Slayer), or $5 (The Golden God).
Stephanie Gaines-Bryant w/Dr. Geoffrey Mount Varner about his book "Home Alive: 11 Must Rules for Surviving Encounters w/Police". Talks about how to deal with a police stop and walk away alive.
In this talk, we introduce the BSTModelKit.jl package, which enables the construction and analysis of biochemical systems theory (BST) models of metabolic and single transduction networks. We demonstrate the capabilities of BSTModelKit.jl by analyzing the thrombin generation dynamics of a population of synthetic patients before and during pregnancy developed from an ongoing study at the University of Vermont supported by the National Institute of Health (NIH).
Biochemical systems theory (BST), developed beginning in the 1960s by Savageau, Voit, and others, is a modeling framework based on ordinary differential equations (ODE) in which biochemical processes are represented using power-law expansions in the system's variables. In this talk, we introduce BSTModelKit.jl, a Julia package dedicated to the automatic generation and analysis of BST models of metabolic and signal transduction networks. BSTModelKit.jl features a simple domain-specific language (DSL) that specifies the model reaction network, methods to estimate steady-state and dynamic solutions to BST models, and methods to conduct global sensitivity analysis of BST model parameters.
We construct and analyze BST models of the thrombin generation dynamics of synthetic patients before and during pregnancy to demonstrate the features of the BSTModelKit.jl package. Women are at higher risk for a blood clot during pregnancy, childbirth, and up to 3 months after delivering a baby. The Centers for Disease Control and Prevention estimates that pregnant women are up to 5 times more likely to experience a blood clot than women who are not pregnant. A synthetic population of pregnant women was developed from patient data to understand better this increased clotting risk. Measurements of 11 coagulation factors involved with the regulation of thrombin generation and measurements of the hormones Estradiol and Progesterone were collected longitudinally from N = 38 women at three visits: V1 non-pregnant, V2 first trimester, and V3 third trimester. A corresponding Thrombin Generation Assay (TGA) was conducted for each patient sample, and parameters describing the dynamics were extracted.
A joint probability model (assumed to be a multivariate normal distribution) was constructed from this matched data by computing the mean vector and covariance arrays from the experimental measurements. The probability model was then used to generate synthetic patient populations (dimension 1k, 10k, and 100k patients) that could be used in subsequent Machine Learning (ML) studies. One such ML study gauged how representative the synthetic population was of the original data. Next, an ordinary differential equation BST model of coagulation dynamics in individual patients was developed from the synthetic population and used to predict the patient TGA parameters. Patient-specific BST model parameters were estimated and used to simulate TGA patient data; the synthetic-patient BST models were consistent with true-patient TGA measurements. Further, global sensitivity analysis of the BST models identified which model parameters controlled the different aspects of the TGA measurements. Finally, by clustering the synthetic and actual patient data, using a radial basis function distance metric, our synthetic population recapitulated the empirically measured differences between the non-pregnant and pregnant states.
The following grants supported this work: The Interaction of Basal Risk, Pharmacological Ovulation Induction, Pregnancy and Delivery on Hemostatic Balance NIH NHLBI R-33 HL 141787 (PI’s Bernstein, Orfeo) and the Pregnancy Phenotype and Predisposition to Preeclampsia NIH NHLBI R01 HL 71944 (PI Bernstein).
Time Stamps:
00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/JuliaCommunity/YouTubeVideoTimestamps
Interested in improving the auto generated captions? Get involved here: https://github.com/JuliaCommunity/YouTubeVideoSubtitles
Jeffrey Varner is a Professor in the Robert Frederick Smith School of Chemical and Biomolecular Engineering at Cornell University. Jeffrey Varner holds a Ph.D degree in Chemical Engineering from Purdue University where he explored modeling and analysis of metabolic networks in the lab of Prof. Ramkrishna. After a postdoc in the Department of Biology at the ETH-Zurich under the direction of Jay Bailey and a research position at Genencor-DuPont, Palo Alto, CA, Prof. Varner joined the faculty of the Chemical and Biomolecular Engineering department at Cornell University as an Assistant Professor in 2006. In the fall of 2011, Prof. Varner was promoted to Associate Professor with tenure, and in 2016 to the rank of Professor. The Varnerlab is interested in modeling and analysis of signal transduction and metabolic networks using kinetic and constraints based modeling techniques. We are also interested in automatic code generation, and model identification using multi-objective optimization. Prof. Varner has received several awards, including an NSF Career Award, and the College of Engineering Teaching Award.
Watch his Systems Seminar talk, 'Mathematical Modeling and Analysis of Metabolic and Information Processing Systems in Biology' here: https://cornell.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=f66a0982-a6df-414a-9d63-4b6e2fa5987b
I'm sure Jeff is horribly embarrassed about outing this to the world...which is funny because people thought he was GAY when he first appeared on Survivor Australia.
But it's good to see the other tribemates back Zeke up
I have a new channel that you can find here: https://www.youtube.com/channel/UCATrdOWnIsWQIHe1F3_EBhQ
Click https://www.patreon.com/EagerTurtle if you would like to consider joining my Patreon for either $1 (The Neat Lady), $3 (The Dragon Slayer), or $5 (The Golden God).