Lunch & Learn - Revision history

Cbalusek3: /* Spring 2015 Abstracts */

2015-04-16T16:42:52Z

Spring 2015 Abstracts

← Older revision		Revision as of 12:42, 16 April 2015
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	References		References
	:(1) A. L. Barabási and R. Albert, "Emergence of scaling in random networks" Science 1999, 286(5439), 509-512.
	:(2) C. Flores, J. Meyer, L. Farr, S. Valverde, and J. S. Weitz, "The statistical structure of host-phage interactions" Proceedings of the National Academy of Sciences 2011, 108, E288-E297.		(1) A. L. Barabási and R. Albert, "Emergence of scaling in random networks" Science 1999, 286(5439), 509-512.
	:(3) C. Flores, S. Valverde, and J. S. Weitz, "Multi-scale structure and geographic drivers of cross-infection within marine bacteria and phages" ISME Journal 2013, 7, 520-532.
			(2) C. Flores, J. Meyer, L. Farr, S. Valverde, and J. S. Weitz, "The statistical structure of host-phage interactions" Proceedings of the National Academy of Sciences 2011, 108, E288-E297.

			(3) C. Flores, S. Valverde, and J. S. Weitz, "Multi-scale structure and geographic drivers of cross-infection within marine bacteria and phages" ISME Journal 2013, 7, 520-532.

	</div>		</div>

Cbalusek3: /* Spring 2015 Abstracts */

2015-04-16T16:42:20Z

Spring 2015 Abstracts

← Older revision		Revision as of 12:42, 16 April 2015
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	References		References
	(1) A. L. Barabási and R. Albert, "Emergence of scaling in random networks" Science 1999, 286(5439), 509-512.		:(1) A. L. Barabási and R. Albert, "Emergence of scaling in random networks" Science 1999, 286(5439), 509-512.
	(2) C. Flores, J. Meyer, L. Farr, S. Valverde, and J. S. Weitz, "The statistical structure of host-phage interactions" Proceedings of the National Academy of Sciences 2011, 108, E288-E297.		:(2) C. Flores, J. Meyer, L. Farr, S. Valverde, and J. S. Weitz, "The statistical structure of host-phage interactions" Proceedings of the National Academy of Sciences 2011, 108, E288-E297.
	(3) C. Flores, S. Valverde, and J. S. Weitz, "Multi-scale structure and geographic drivers of cross-infection within marine bacteria and phages" ISME Journal 2013, 7, 520-532.		:(3) C. Flores, S. Valverde, and J. S. Weitz, "Multi-scale structure and geographic drivers of cross-infection within marine bacteria and phages" ISME Journal 2013, 7, 520-532.

	</div>		</div>

Cbalusek3: /* Spring 2015 Abstracts */

2015-04-16T16:42:04Z

Spring 2015 Abstracts

← Older revision		Revision as of 12:42, 16 April 2015
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	==Spring 2015 Abstracts==		==Spring 2015 Abstracts==

			<span id="Song2014"></span>
			<div style="margin-top: 5px; margin-bottom: 5px; border: 1px; border-style: dashed; padding: 10px; background-color:#F0F0F0;border-color:#33ADFF">
			'''16 April 2015'''

			Chung Yin "Joey" Leung

			'''Conflicting Attachment and the Growth of Bipartite Networks'''

			Abstract:
			Network growth models have become an indispensable part of the study of networks. In these models, the network grows by sequential addition of new nodes, where the connectivity of each newly added node is determined by the existing network connectivity and a set of predefined rules describing the network growth mechanisms. A number of network growth mechanisms has been proposed to explain the emergence of structural properties observed in real networks. For example, the widely-studied preferential attachment mechanism assumes that a newly added node is more likely to link to an existing node that is already well-connected. Such a mechanism can explain the power-law degree distribution observed in complex scale-free networks [1]. However, the growth mechanisms of many networks are incompatible with preferential attachment. In many bipartite systems composed of two types of agents that interact, there exists a fundamental conflict of interests as to the preferred level of connectivity. For example, in an interaction network between virus (phage) and microbe (bacteria) where a link denotes the ability for a given phage to infect a bacteria, a high level of connectivity may be beneficial for a phage but detrimental to a bacteria. Recent studies have revealed intriguing structural properties in these infection networks. They exhibit a nested pattern where relatively highly-resistant bacteria are infected by generalist phages and relatively susceptible bacteria are infected by generalist and specialist phages [2]. In addition, they can exhibit modular patterns with groups consisting of phages and bacteria that interact strongly within the group but not between groups [3]. The mechanism for the emergence of these properties is not well understood. We propose a network growth model with a conflicting attachment mechanism inspired by the evolution of phage-bacteria interactions. We find that the resulting networks reproduce realistic patterns found in empirical data including nestedness, modularity, and a nested-modular pattern where modularity is observed at the network scale and nestedness is observed at the module scale. We study the role of conflicting interests in shaping network structure and discuss ways to incorporate greater realism in linking growth process to pattern.


			References
			(1) A. L. Barabási and R. Albert, "Emergence of scaling in random networks" Science 1999, 286(5439), 509-512.
			(2) C. Flores, J. Meyer, L. Farr, S. Valverde, and J. S. Weitz, "The statistical structure of host-phage interactions" Proceedings of the National Academy of Sciences 2011, 108, E288-E297.
			(3) C. Flores, S. Valverde, and J. S. Weitz, "Multi-scale structure and geographic drivers of cross-infection within marine bacteria and phages" ISME Journal 2013, 7, 520-532.

			</div>

	<span id="Song2014"></span>		<span id="Song2014"></span>

Cbalusek3: /* Spring 2015 Abstracts */

2015-04-16T16:40:26Z

Spring 2015 Abstracts

← Older revision		Revision as of 12:40, 16 April 2015
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	==Spring 2015 Abstracts==		==Spring 2015 Abstracts==

			<span id="Song2014"></span>
			<div style="margin-top: 5px; margin-bottom: 5px; border: 1px; border-style: dashed; padding: 10px; background-color:#FFFFFF;border-color:#33ADFF">
			'''9 April 2015'''

			Douglas "Bo" Broadwater --- Kim Lab

			'''The Effects of Mismatch Position on DNA Strand Displacement Rate'''

			DNA strand displacement is a reaction involving three single strands of DNA. It occurs when one single strand of DNA fully hybridizes to a partially duplexed complement. DNA strand displacement is essential to two of the most critical operations in biology, DNA repair and homologous recombination. It is also utilized in the field of nanotechnology in diverse areas such as DNA motors and DNA computation. In this week's PoLS meeting, I will discuss our work towards tuning the overall rate of strand displacement by varying the position of a single nucleotide mismatch. The ability to tune the displacement rate is important because it has applications in identifying single nucleotide variants in mRNA transcripts. I will provide experimental evidence of a non-trivial relationship between strand displacement rate and mismatch position. Finally, I will posit a model that explains the origins of the complex rate behavior as being due to both secondary structure and mismatch position.

			</div>

			<span id="Song2014"></span>
			<div style="margin-top: 5px; margin-bottom: 5px; border: 1px; border-style: dashed; padding: 10px; background-color:#F0F0F0;border-color:#33ADFF">
			'''2 April 2015'''

			Travis Tune --- Sponberg Lab

			'''Energetic Versatility of Muscle'''

			Muscle is a unique material which has the ability to operate as a spring, motor, brake, or strut which are characterized by a muscle’s workloop. In a typical workloop experiment, force and length of a muscle are plotted against each other while the muscle undergoes oscillation while being activated under physiological conditions. A muscle’s workloop can be altered by changing any of a number of physiological inputs such as temperature, phase or frequency of activation, or operating length. This is what is meant by “Energetic Versatility of Muscle”- the ability of muscle to alter its role quickly and with low energy cost. In this talk I will give an overview of what parameters are known to alter muscle workloops and then will introduce a system of two muscles whose workloops are not explained by our current understanding of muscle physiology. I will then discuss the structure of the muscle as a potential source of variation of workloops. Because skeletal muscle is a highly ordered structure, we can use the technique of x-ray diffraction to examine the lattice structure of muscle. To do this, we traveled to Argonne National Lab to make use of the Advanced Photon Source x-ray beamline. Our early results show what may be a difference in the lattice spacing of the two muscles. We also will perform a frequency analysis on muscle, from which we can extract rates which are related to the molecular processes which are responsible for muscle’s force generation.

			</div>

	<span id="Song2014"></span>		<span id="Song2014"></span>

Cbalusek3: /* Spring 2015 Abstracts */

2015-04-16T16:37:37Z

Spring 2015 Abstracts

← Older revision		Revision as of 12:37, 16 April 2015
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	<span id="Song2014"></span>		<span id="Song2014"></span>
	<div style="margin-top: 5px; margin-bottom: 5px; border: 1px; border-style: dashed; padding: 10px; background-color:#FFFFFF;border-color:#33ADFF">		<div style="margin-top: 5px; margin-bottom: 5px; border: 1px; border-style: dashed; padding: 10px; background-color:#FFFFFF;border-color:#33ADFF">
	'''12 March 2015'''		'''26 March 2015'''

	James Waters --- Kim Lab		James Waters --- Kim Lab

Cbalusek3: /* Spring 2015 Abstracts */

2015-04-16T16:37:24Z

Spring 2015 Abstracts

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	'''12 March 2015'''		'''12 March 2015'''

	~~'''Cellular mechanisms for QRS alternans in the heart'''~~		James Waters --- Kim Lab

	Abstract:		'''Simulation of fluctuating entropic force by kinetic sampling'''
	~~Alternans~~ in ~~the electrocardiogram~~ of the ~~heart often precede sudden cardiac death~~. ~~To analyze~~ the ~~conditions that allow for alternans, scientists examine dynamics~~ at the ~~cellular level~~. ~~For T-wave alternans~~, ~~it has been confirmed~~ that the ~~source is due to an alternating action potential duration at~~ the ~~cellular level~~. ~~However,~~ the ~~cellular mechanisms~~ for ~~QRS alternans have not been well studied~~.
	~~We propose that the source~~ of ~~QRS alternans~~ is ~~due to action potential amplitude alternation at~~ the ~~cellular level~~. ~~First, we created a simple model~~ that ~~reproduces this effect. Next~~, ~~we derived a method to analyze~~ the ~~criteria for amplitude alternation~~ in ~~this simple model~~. ~~Our results show~~ that ~~our method of analysis is correct in predicting~~ the ~~conditions for alternans~~.		Abstract: A polymer chain when pinned to a point or a plane exerts a force on the pinning point in thermal equilibrium. From a thermodynamic point of view, this force arises as the chain tries to minimize its free energy at constant temperature. Due to the hard constraint at the pinning point, calculation of this entropic force is not a trivial problem in statistical mechanics. Here, we introduce a novel kinetic sampling method that can produce the equilibrium distribution of instantaneous forces exerted by a terminally pinned polymer. We represent a generic flexible chain using the canonical bead-rod model and perturb both the positions and momenta of the beads compatible with the spatial constraints and the Boltzmann distribution of total energy. We then calculated the constraint force for each conformation using Lagrangian dynamics. The mean of this force distribution is consistent with the force estimated from the partition function. Unlike the mean that quickly plateaus at tens of monomers, the skewness of the distribution keeps increasing in the range of chain lengths tested. This result suggests that longer chains exert large pulling forces at the pinning point more frequently than short chains. Our work provides insights into the mechanistic origin of entropic forces, and a computational tool applicable to simulations of constrained systems

	</div>		</div>

Cbalusek3: /* Spring 2015 Abstracts */

2015-04-16T16:36:22Z

Spring 2015 Abstracts

← Older revision		Revision as of 12:36, 16 April 2015
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	<span id="Song2014"></span>		<span id="Song2014"></span>
	<div style="margin-top: 5px; margin-bottom: 5px; border: 1px; border-style: dashed; padding: 10px; background-color:#FFFFFF;border-color:#33ADFF">		<div style="margin-top: 5px; margin-bottom: 5px; border: 1px; border-style: dashed; padding: 10px; background-color:#FFFFFF;border-color:#33ADFF">
	'''~~5 February~~ 2015'''		'''12 March 2015'''

	'''Cellular mechanisms for QRS alternans in the heart'''		'''Cellular mechanisms for QRS alternans in the heart'''

Cbalusek3: /* Spring 2015 Abstracts */

2015-04-16T16:36:01Z

Spring 2015 Abstracts

← Older revision		Revision as of 12:36, 16 April 2015
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	==Spring 2015 Abstracts==		==Spring 2015 Abstracts==

			<span id="Song2014"></span>
			<div style="margin-top: 5px; margin-bottom: 5px; border: 1px; border-style: dashed; padding: 10px; background-color:#FFFFFF;border-color:#33ADFF">
			'''5 February 2015'''

			'''Cellular mechanisms for QRS alternans in the heart'''

			Abstract:
			Alternans in the electrocardiogram of the heart often precede sudden cardiac death. To analyze the conditions that allow for alternans, scientists examine dynamics at the cellular level. For T-wave alternans, it has been confirmed that the source is due to an alternating action potential duration at the cellular level. However, the cellular mechanisms for QRS alternans have not been well studied.
			We propose that the source of QRS alternans is due to action potential amplitude alternation at the cellular level. First, we created a simple model that reproduces this effect. Next, we derived a method to analyze the criteria for amplitude alternation in this simple model. Our results show that our method of analysis is correct in predicting the conditions for alternans.

			</div>

	<span id="Song2014"></span>		<span id="Song2014"></span>

Cbalusek3: /* Spring 2015 Abstracts */

2015-04-08T16:02:37Z

Spring 2015 Abstracts

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 ==Spring 2015 Abstracts==
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Cbalusek3: /* Spring 2015 Schedule */

2015-04-08T15:58:35Z

Spring 2015 Schedule

← Older revision		Revision as of 11:58, 8 April 2015
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	! 26 February		! 26 February
	!		!
	[[#Souslav2015\| Dr. Anton Souslov --- Goldbart Lab ]]		[[#Souslav2015\| Dr. Anton Souslov --- Goldbart Lab --- Snow Day, Campus Closed ]]
	\|-		\|-
	! 5 March		! 5 March