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Evaluations for the MCell 2014 Workshop

Evaluations for the Computational Methods for Spatially Realistic Microphysiological Simulations Workshop

April 2014

Workshop details:   Home  Agenda  Instructors    Evaluations   Google Maps

 

Participants were asked to evaulate the workshop in the following areas. Numeric scales ranged from 1 -5, with one being the lowest satisfaction and 5 being the highest.

The Cell Modeling workshop was very valuable for my current/future research

1 2 3 4 5 Average score
- - - 2 7 4.8

I would recommend the Cell Modeling Workshop to my colleagues

1 2 3 4 5 Average score
- - 1 2 6 4.6

The instructors and teaching assistants were well prepared.

1 2 3 4 5 Average score
- - - 2 7 4.8

The instructors and teaching assistants were helpful and assisted me with my problems and questions.

1 2 3 4 5 Average score
- - - 2 7 4.8

The online tutorials were useful (www.mcell.org/tutorials).

1 2 3 4 5 Average score
- - 3 4 3 4.1

Which aspect of the workshop was most useful to you?

  • The fact there many instructors were around to help. All of them knew how to trouble shoot. Everyone was cheerful, positive and willing to help. 
  • The application of blender into Mcell offered a really simple and intuitive way to create a topology for the system.
  • CellOrganizer and Cellblender
  • It is great to have learned how to navigate in CellBlender.
  • Knowing that something like CellOrganizer exists has inspired various project ideas.
  • The mCell lab class with Justin, and the extra help from the instructors especially Tom.
  • hands on tutorial and  discussions with classmates  and instructors.
  • 1. Hands-on tutorial of Blender and Mcell. Blender is very cool, and fun to play with!
    2. Modeling workflow and the relationships between these different spatial modeling tools. It's nice and very helpful to have a big picture in mind, and getting to know how people in computational field think about biology.

 

What workshop topics would you like to see emphasized more in the future?

  • It would be really interesting if each day we worked on a third of a project that would be complete by the end of the workshop. The pdf tutorial hinted somewhat at this but I don't think we ended up going through with it. Creating a project that incorporates all that we learned with results would give a nice take home piece to look back and refer to, as well as show how each of these tools come together.
  • Direction of promising research
  • Hands-on MDL scripting tutorial session.
  • How to actually make useful models in mCell. It was cool to get an overview, but without extra help 1 day on each software package is not enough to actually go home and use it independently.
  • It would be nice to have more social events.
  • Maybe we can have simpler examples in hand-on tutorial session, especially for cell blender and cell organizer. It's nice to see super cool examples during the lecture, but as beginners it can be frustrated handling a very complex model.  It would also be a good idea to we can have a complete experience in combining the three tools together and really think about spatially effect during the process. For example, maybe start from day1, we can get familiar with Blender, and start thinking about a spatial toy model (involving just 2 or 3 reactions and some simple geometry), then on day2 we can set up the model in cBNGL and run it in Blender, and in day3 play with the parameters and different geometries trained in CellOrganizer.

Other comments

  • It would help to have - Notepads - Pens
  • I really learned a lot and I don't think I would have been introduced to these tools otherwise. Whether or not they I will use them depends on what I pursue in the future, but it is an exciting field to say the least
  • I really admire the effort your group is making to not only produce great tools, but to make them smooth and accessible and easy to use. Lots of researchers write clever software, but to make it easy to use is much harder and it's wonderful that you prioritize it.
  • This workshop is very helpful for solving problems in my research. Moreover, it gives me an opportunity to know the latest tools developed for biology research. Everyone is extremely helpful. I wish the computational tools can be more broadly used as more knowledge is gained from experiments. I will follow up MCell, maybe through the forum.
  • 1. I think people would like to have printer around in the future. 2. Many thanks to all instructors and assistants! I had a great time in this workshop:)

The presentation was clear and well structured.

1 2 3 4 5 Average score
- - - 1 8 4.9

The lecture taught me the basics of building MCell Models

1 2 3 4 5 Average score
- - - 1 8 4.9

I expect that MCell modeling will be important to my current or planned research projects.

1 2 3 4 5 Average score
- - 1 1 7 4.7

Comments or Suggestions

  • I hope more can be showed for how to combine MCell codes and Cell blender.

The presentation was clear and well structured.

1 2 3 4 5 Average score
- - - 1 8 4.9

The lecture taught me the basics of MCell methods for diffusion and reaction.

1 2 3 4 5 Average score
- - - 2 7 4.8

Comments

  • The videos are very impressive.

Ease of use of CellBlender

1 2 3 4 5 Average score
- 1 2 2 4 4.0

I expect that CellBlender will be important to my current or planned research projects.

1 2 3 4 5 Average score
- - - 4 4 4.5

In your opinion, what aspect of CellBlender needs the most improvement (e.g. model design, running simulations, analysis)?

  • It is not always clear what CellBlender is doing
  • it needs an easy button for cancelling mcell simulation when it is stuck
  • Running multiple simulations while making incremental changes would be cool design and analysis
  • analysis
  • Making the physics built into MCell more manipulable would be helpful.

Are any features missing from CellBlender or MCell which are crucial for your workflow? Please elaborate.

  • It would be nice for Cell Blender to follow some "steps". It is there but would help if it were just clearer in the tutorials with additional pictures. You could also have a small video uploaded that shows each screen shot and how each step goes into play. Additional it would help in the video to talk about hotkeys, and common linux issues encountered by folks still trying to get familar with the linux environment.
  • It is hard to say as I am just starting

Comments or suggestions

  • I think it was a great first day, but a shame we didn't get to do more modelling. Another day on mCell would have suited my goals.
  • Very cool to see the data gets animated. it can be good for science education too

Clarity of Presentation

1 2 3 4 5 Average score
- - 2 3 4 4.2

How much you learned

1 2 3 4 5 Average score
- - 1 4 4 4.3

Usefulness of rule-based modeling to your current or planned research projects.

1 2 3 4 5 Average score
- 2 4 1 2 3.3

Comments

  • I have no immediate plans to model large networks, but I do work with protein networks, so I might use it in the future. The lecture was challenging but I understood the advantages of rule-based modelling by the end, and it was very interesting.
  • I can see this tool is very useful for my biochemistry and development friend.

Clarity of presentation

1 2 3 4 5 Average score
- - 2 3 4 4.2

How much you learned

1 2 3 4 5 Average score
- - 1 5 3 4.2

Pace of the tutorial

Too fast About right
4 5

Ease of use of RuleBender

1 2 3 4 5 Average score
- - 4 4 1 3.7

Usefulness of RuleBender to your current or planned research projects.

1 2 3 4 5 Average score
- 2 4 1 2 3.3

Comments

  • RuleBender is a powerful tool but the amount of material covered in a day is very dense. It would be nice to study the same exact problem in MCell on day1 and cover it using RuleBender on day2. This, before you progress to more specific problems.

    Also, it will help to come up with alternate examples (other scales?) that dont study just intracellular pathways and protein dynamics.

  • Jose was too quick on the file openings, but he was very responsive when asked to slow down. I was impressed with his patience. The actual coding part of the lab was quite clear and I had no problem following. I quite liked the lab structure, starting by building a small model then playing with a larger one. The only thing missing was that I don't entirely follow what one would do with the out-putted data (i.e. what kind of hypothesis would you address and how).
  • It certainly made modeling reactions easy.

Are there any additional features that you would like to have in RuleBender or in the interface with CellBlender/MCell? Please elaborate.

  • I am still not sure how to write reactions in Cellblender by using RuleBender
  • I just wonder how the diffusion coefficient is defined when cBNGL is translated in to SBML? Can we specify them manually?

Please add any other suggestions you have for improving Day 2 of the workshop.

  • A lot of time was spent on the slides covering RuleBender but it was a very specific problem used to convey concepts on RuleBender. It would be useful to have a generic model that explains the audience about RuleBender and then go over a specific problem.
  • After we import the complex cell , we didn't get a chance to build reactions and visualize them in CellBlender

Evaluations for the MCell 2015 Workshop

Evaluations for the Computational Methods for Spatially Realistic Microphysiological Simulations Workshop

April 2015

 

Participants were asked to evaulate the workshop in the following areas. Numeric scales ranged from 1 -5, with one being the lowest satisfaction and 5 being the highest.

The Cell Modeling workshop was very valuable for my current/future research

1 2 3 4 5 Average score
- - 1 3 12 4.7

I would recommend the Cell Modeling Workshop to my colleagues

1 2 3 4 5 Average score
- - - 3 13 4.8

The instructors and teaching assistants were well prepared.

1 2 3 4 5 Average score
- - 2 7 7 4.3

The instructors and teaching assistants were helpful and assisted me with my problems and questions.

1 2 3 4 5 Average score
- - 1 3 12 4.7

The online tutorials were useful (www.mcell.org/tutorials).

1 2 3 4 5 Average score
- - - 9 7 4.4

Which aspect of the workshop was most useful to you?

  • Learning getting scientific figure from the biological study
  • The combination of theory and tutorials. I think on their own, each would be useful, but not nearly as useful.
  • Exposure to recent developments especially CellBlender. Opportunity to interact with developers. New modeling possibilities even though I may not use them.
  • For me (a biologist with little computational/modeling experience) it the most useful were (tie): -very basic aspects (e.g. programming theory/ nomenclature/ logic/ workflow) -afternoons dedicated to small group (or ""1-on-1"") work with workshop instructors and TAs.
  • I can get clear ideas of cell modeling and the latest progress.
  • Learning about MCell and CellBlender
  • The hands-on time and discussions with the instructors.
  • Most of the topics were knew to me and as a result I learned a lot!
  • Hands on lab exercises were most useful
  • MCell and CellBlender
  • Introductory seminars for MCell and BioNetGen (morning sessions), Introductory tutorials, Undirected hands-on time with programs"
  • MCell internals, CellBlender material, discussions with the developers.
  • Diffusion simulation methods and what we can get out of it.
  • The help of each assistant was exceptional good. There was always someone who could help out at every topic you can imagine.
  • The hands on tutorials in the computer room were most useful. However, the instructors moved too quickly, and there was little to no time to work on our own research projects - perhaps adding an optional forth day for apply the tools to personal research projects would be helpful. The instructors were very good at helping anyone out who had fallen behind, but there were typically not enough instructors to go around.
  • The first day was most useful to me, both talks and labs.

 

What workshop topics would you like to see emphasized more in the future?

  • More time on the specific package(s) that I will be using - could perhaps be specified via a pre-meeting phone call/ Skype session (to help the instructors/TAs understand the detailed goals of individual participants(?))
  • Explanation of details of modeling by using any realistic model.
  • None, the workshop was pretty close to perfect.
  • No idea!
  • More scheduled time for working on independent projects with assistance from staff.
  • Basic principles upon which the MCell etc. is based. There is a great danger in using these tools "blindly", and the danger increases as they become more user-friendly and attract wider user base.
  • A smaller research example of diffusion simulation.
  • I would recommend even more time for practical courses to train the software on your own.
  • I would spend less time lecturing about the mathematics behind the tools and more time lecturing about practical problems/questions that may arise when using the tools.
  • Larger focus on MCell. More lab exercises with specific tasks to accomplish.

Other comments

  • Be more realistic about the timing of lectures and tutorials. It ended up working, but it seemed a little chaotic at times.
  • Very nice atmosphere. Everyone very interested in topics and paying full attention.
  • Excellent and valuable workshop.
  • Seminars relating to recent thesis work were not useful and related demos did not work well on personal laptops.
  • First and third days were much better than the second day, especially the afternoon tutorial.
  • Overall, I liked Cell Modeling workshop very much. I was not too happy with the second afternoon. Instructors were going through material too fast.

The presentation was clear and well structured.

1 2 3 4 5 Average score
- - - 2 14 4.9

The lecture taught me the basics of building MCell Models

1 2 3 4 5 Average score
- - 1 3 12 4.7

I expect that MCell modeling will be important to my current or planned research projects.

1 2 3 4 5 Average score
- - 2 3 11 4.6

Comments or Suggestions

  • See earlier comment on parallel sessions.
  • 1. One day is not enough for this material.

    2. MDL deserves more time: There may be exceptions (very simple models) but it is unlikely that one could (or even should) get by entirely without writing or at least thorough understanding of MDL. When the model geometries have to be numerically accurate, CellBlender cannot easily create them anyway. So it's far more important that CellBlender reads and correctly displays every bit of legal MDL than that it writes MDL as well. Except for the simplest cases, it's also more time-consuming and error-prone to manage a collection of dialog boxes than to edit an MDL file.

The presentation was clear and well structured.

1 2 3 4 5 Average score
- - - 3 13 4.8

The lecture taught me the basics of MCell methods for diffusion and reaction.

1 2 3 4 5 Average score
- - 1 3 13 4.7

Comments

  • See earlier comment on parallel sessions.
  • More time was needed, especially to explain the algorithms behind more complicated reactions.

Ease of use of CellBlender

1 2 3 4 5 Average score
- - 7 5 4 3.8

I expect that CellBlender will be important to my current or planned research projects.

1 2 3 4 5 Average score
- - 3 3 10 4.4

In your opinion, what aspect of CellBlender needs the most improvement (e.g. model design, running simulations, analysis)?

  • Analysis: changing scales in graph outputs
  • Not possible to say without more familiarity
  • Drop down menus for some elements
  • Analysis
  • None, I think most of the efforts at improvement that were discussed are well targeted.
  • Model design
  • Model design, access to error messages
  • It should read and display any legal MDL!
  • Expand the library of cell shapes and organelles and make the export to SBML easier.

Are any features missing from CellBlender or MCell which are crucial for your workflow? Please elaborate.

  • In Window, some menus do not appear. For example, matplotlib for plot does not appear at my laptop
  • Not possible to say without more familiarity
  • Various methods for dynamics
  • It seems work on most of the missing features is currently underway.
  • n/a
  • Concentration-based simulation
  • Running multiple instances of MCell through CellBlender with different parameters

Comments or suggestions

Clarity of Presentation

1 2 3 4 5 Average score
- - 3 7 6 4.2

How much you learned

1 2 3 4 5 Average score
- - 4 7 5 4.1

Comments

  • Hands on Rulebender need much more time for the beginner like me to learn fully. I think it would start 11 AM at least.
  • Talk could have been a bit tighter in organization and timing but still very interesting.
  • The only confusions came when Jim's very well-organized (!) lecture on the basics of RBM got off onto rather lengthy (1-5 minutes) tangents. They got reeled in eventually. Shorter tangents (<1 min) weren't a problem
  • It's a difficult design task but the scripting language seemed a bit "young and awkward" at this point (compared to, say, MDL).
  • I didn't use RuleBender untill now so I don't know if this tool will be used in my further research. The tool itself seemed very powerful and useful!

Clarity of presentation

1 2 3 4 5 Average score
- - 3 8 5 4.1

How much you learned

1 2 3 4 5 Average score
1 2 5 5 4 3.6

Pace of the tutorial

Too fast About right
5 7

Ease of use of RuleBender

1 2 3 4 5 Average score
- 1 6 5 4 3.8

Usefulness of RuleBender to your current or planned research projects.

1 2 3 4 5 Average score
- 3 6 3 4 3.5

Comments

  • It was too fast. In addition to that, assigned time is so short that we (maybe) could follow them easily.
  • Demonstration was buggy and too fast-paced for trouble shooting.
  • Without prior knowledge, it's impossible to listen to a talk, watch the presentation, and do the tasks on your computer, all at the same time. The tutorial could be done similarly to the first day tutorials.

Are there any additional features that you would like to have in RuleBender or in the interface with CellBlender/MCell? Please elaborate.

  • For example, the lecturer gives a simple biochemical reaction and the students apply the RuleBender's rule to it
  • Allow binding interactions between molecules in two different membrane compartments, e.g. binding of ligand and receptors on two opposing cell surfaces.

Please add any other suggestions you have for improving Day 2 of the workshop.

  • Of the three days, this is most important. As I said just before, the time for Hands-on needs much more than this year.
  • I think it would help if tutorials were debugged more and were less ambitious.
  • More time for undirected hands-on work would be useful, particularly if staff were available for assistance.
  • From my (perhaps narrow) point of view, the RuleBender concept is relatively simple, the rest being the mechanics of doing it. Since the concepts and underlying algorithms are the most important things to learn, I'd suggest shortening this section to 1/2 day and use the time for MCell algorithms, which are conceptually more difficult.
  • Try afternoon sessions on naive computer-non-savvy audience.

Hands-on Computational Biophysics and Cell Modeling Workshop Testimonials

We are very proud of the workshops presented by the MMBios team. Here's what attendees have to say:

“Loved this workshop - I feel like I learned a lot and will be using most of these techniques in my own research.”

“[The workshop] exposed me to computational biology and now I am very excited to explore modeling dynamics and other computational techniques in the future.”

“Fantastic workshop, exactly what was needed to jumpstart research.”

“The workshop was outstanding, overall I appreciated the individual interaction w/ the instructors. The breadth of the workshop was great for introducing new tools for my research. The tutorials are also excellent and useful for continuing study after the workshop. Thank you.”

“Overall, this workshop was a great experience. It was very informative and every one of the instructors and TAs was knowledgeable, kind, and helpful. I did learn a lot and am looking forward to use these tools and techniques for my research.“

“I really learned a lot and I don't think I would have been introduced to these tools otherwise.“

“I really admire the effort your group is making to not only produce great tools, but to make them smooth and accessible and easy to use. Lots of researchers write clever software, but to make it easy to use is much harder and it's wonderful that you prioritize it.”

“This workshop is very helpful for solving problems in my research. Moreover, it gives me an opportunity to know the latest tools developed for biology research.  Everyone is extremely helpful.”

“Concrete examples are easier for an experimentalist (me) to grok.  There were several of these - thanks!”

“The fact there many instructors were around to help. All of them knew how to trouble shoot. Everyone was cheerful, positive and willing to help.”

“I can see this tool is very useful for my biochemistry and development friend.”

“Most of the topics were new to me and as a result I learned a lot!”

“The help of each assistant was exceptionally good. There was always someone who could help out at every topic you can imagine.”

“Excellent and valuable workshop.”

 

Registration: Cell Modeling Workshop 2016

{chronoforms}CellModeling2016{/chronoforms}

Research Highlights

 

Direct coupling of oligomerization and oligomerization-driven endocytosis of the dopamine transporter to its conformational mechanics and activity

The Bahar (TR&D1) and Sorkin (DBP3) labs published an article in the Journal of Biological Chemistry, selected as one of JBC's "Editors' Picks. Our results demonstrate a direct coupling between conformational dynamics of DAT, functional activity of the transporter and its oligomerization leading to endocytosis. The high specificity of such coupling for DAT makes the TM4-9 hub a new target for pharmacological modulation of DAT activity and subcellular localization. (Read more)

 

 

Differences in the intrinsic spatial dynamics of the chromatin contribute to cell differentiation

Comparison with RNA-seq expression data reveals a strong overlap between highly expressed genes and those distinguished by high mobilities in the present study, in support of the role of the intrinsic spatial dynamics of chromatin as a determinant of cell differentiation. (Read more)

 

 

Nanoscale co-organization and coactivation of AMPAR, NMDAR, and mGluR at excitatory synapses

Work by TR&D2 Investigators and collaborators provide insights into the nanometer scale organization of postsynaptic glutamate receptors using a combination of dual-color superresolution imaging, electrophysiology, and computational modeling. (Read more)

 

 

Parallel Tempering with Lasso for model reduction in systems biology

TR&D3 Investigators and collaborators develop PTLasso, a Bayesian model reduction approach that combines Parallel Tempering with Lasso regularization, to automatically extract minimal subsets of detailed models that are sufficient to explain experimental data. On both synthetic and real biological data, PTLasso is an effective method to isolate distinct parts of a larger signaling model that are sufficient for specific data. (Read more)

 

Image-derived models of cell organization changes during differentiation and drug treatments

Our work on modeling PC12 cells undergoing differentiation into neuron-like morphologies (under C&SP11, completed) has been published in Molecular Biology of the Cell. We have also made the large dataset of 3D images collected in that study available through Dryad. (Read more)

 

Monoamine transporters: structure, intrinsic dynamics and allosteric regulation

T&RD1 investigators Mary Cheng and Ivet Bahar published an invited review article in Nature Structural & Molecular Biology, addressing recent progress in the elucidation of the structural dynamics of MATs and their conformational landscape and transitions, as well as allosteric regulation mechanisms. (Read more)

Trimerization of dopamine transporter triggered by AIM-100 binding

The Bahar (TR&D1) and Sorkin (DBP3) labs explored the trimerization of dopamine transporter (DAT) triggered by a furopyrimidine, AIM-100, using a combination of computational and biochemical methods, and single-molecule live-cell imaging assays. (Read more)

Pre-post synaptic alignment through neuroligin-1 tunes synaptic transmission efficiency

TR&D2 investigators and collaborators describe organizing role of neuroligin-1 to align post-synaptic AMPA Receptors with pre-synaptic release sites into trans-synaptic “nano-columns” to enhance signaling.(Read more)

Inferring the Assembly Network of Influenza Virus

In an article in PLoS Computational Biology, MMBioS TR&D4 members Xiongto Ruan and Bob Murphy collaborated with Seema Lakdawala to address this question of the assembly network of the Influenza virus.(Read more)

PINK1 Interacts with VCP/p97 and Activates PKA to Promote NSFL1C/p47 Phosphorylation and Dendritic Arborization in Neurons

Our findings highlight an important mechanism by which proteins genetically implicated in Parkinson’s disease (PD; PINK1) and frontotemporal dementia (FTD; VCP) interact to support the health and maintenance of neuronal arbors.(Read more)

Improved methods for modeling cell shape

In a recent paper in Bioinformatics, Xiongtao Ruan and Bob Murphy of TR&D4 addressed the question of how best to model cell and nuclear shape.(Read more)

New tool to predict pathogenicity of missense variants based on structural dynamics: RHAPSODY

We demonstrated that the analysis of a protein’s intrinsic dynamics can be successfully used to improve the prediction of the effect of point mutations on a protein functionality. This method employs ANM/GNM tools (Read more)

New method for investigating chromatin structural dynamics.

By adapting the Gaussian Network Model (GNM) protein-modeling framework, we were able to model chromatin dynamics using Hi-C data, which led to the identification of novel cross-correlated distal domains (CCDDs) that were found to also be associated with increased gene co-expression.  (Read more)

 

Structural elements coupling anion conductance and substrate transport identified

We identified an intermediate anion channeling state (iChS) during the global transition from the outward facing (OF) to inward facing state (IFS). Our prediction was tested and validated by experimental study conducted in the Amara lab (NIMH). Critical residues and interactions were analyzed by SCAM, electrophysiology and substrate uptake experiments (Read more)

Integrating MMBioS technologies for multiscale discovery

TR&D teams driven by individual DBPs are naturally joining forces, integrating their tools to respond to the needs of the DBP, and creating integrative frameworks for combining structural and kinetic data and computing technologies at multiple scales.  (Read more)

 

Large scale visualization of rule-based models.

Signaling in living cells is mediated through a complex network of chemical interactions. Current predictive models of signal pathways have hundreds of reaction rules that specify chemical interactions, and a comprehensive model of a stem cell or cancer cell would be expected to have many more. Visualizations of rules and their interactions are needed to navigate, organize, communicate and analyze large signaling models.  (Read more)

Integration of MCellR into MCell/CellBlender

Using spatial biochemical models of SynGAP/PSD95, MMBioS investigators were able to merge the MCellR code-base with the MCell code-base and validate its utility and correctness of this sophisticated technology now easily accessible through the MCell/CellBlender GUI.  (Read more)

 

csp29

Causal relationships of spatial distributions of T cell signaling proteins

The idea is to identify a relationship in which a change in the concentration of one protein in one cell region consistently is associated with a change in the concentration of another protein in the same or a different region. We used the data from our Science Signaling paper reported last year to construct a model for T cells undergoing stimulation by both the T cell receptor and the costimulatory receptor. (Read more...)

T-Cell Receptor Signaling

BioNetGen modeling helps reveal immune system response decision

To attack or to let be is an important decision that our immune systems must make to protect our bodies from foreign invaders or protect bodily tissues from an immune attack. Using modeling and experiments, we have painted a sharper picture of how T cells make these critical decisions.  (Read more)

 

 

distancecell

Tools for determining the spatial relationships between different cell components

An important task for understanding how cells are organized is determining which components have spatial patterns that are related to each other.Read more

 

4d rtd

Pipeline for creation of spatiotemporal maps

Using a combination of diffeomorphic methods and improved cell segmentation, we developed a CellOrganizer pipeline for use in DPB4 to construct models of the 4D distributions of actin and 8 of its regulators during the response of T cells to antigen presentation. Read more

 

Multi-scale Hybrid Methodology

The hybrid methodology, coMD, that we have recently developed [1] has been recently extended to construct the energy landscape near the functional states of LeuT (Fig 1) [2]. This is the first energy landscape constructed for this NSS family member. Read more

 


Insights into the cooperative dynamics of AMPAR

Comparative analysis of AMPAR and NMDAR dynamics reveals striking similarities, opening the way to designing new modulators of allosteric interactions. Read more


Improved Sampling of Cell-Scale Models using the WE Strategy

The WE strategy for orchestrating a large set of parallel simulations has now been extended to spatially resolved cell-scale systems. The WESTPA implementation of WE has been used to control MCell simulations, including models built using a BioNetGen-CellOrganizer pipeline for situating complex biochemistry within spatially realistic cell models. Read more

Mouse visual cortex
Anatomy and Function of an Excitatory Network in the Visual Cortex

MMBioS researcher Greg Hood’s collaboration with Wei-Chung Allen Lee of Harvard University and R. Clay Reid of the Allen Institute for Brain Science concerning the reconstruction of an excitatory nerve-cell network in the mouse brain cortex at a subcellular level using the AlignTK software has been published in Nature. Read more

 

Molecular Mechanism of Dopamine Transport by hDAT

Dopamine transporters (DATs) control neurotransmitter dopamine (DA) homeostasis by reuptake of excess DA, assisted by sodium and chloride ions. The recent resolution of DAT structure (dDAT) from Drosophila permits us for the first time to directly view the sequence of events involved in DA reuptake in human DAT (hDAT). Read more

 

 

 

figure good 170Synaptic Facilitation Revealed

An investigation of several mechanisms of short-term facilitation at the frog neuromuscular junction concludes that the presence of a second class of calcium sensor proteins distinct from synaptotagmin can explain known properties of facilitation. Read more

 

langmead2 200Sparse Graphical Models of Protein:Protein Interactions

DgSpi is a new method for learning and using graphical models that explicitly represent the amino acid basis for interaction specificity and extend earlier classification-oriented approaches to predict ΔG of binding. Read more

 

Picture1 180Advancing Parallel Bio-simulations

A new non-Markovian analysis can eliminate bias in estimates of long-timescale behavior, such as the mean first-passage time for the dissociation of methane molecules in explicit solvent. Read more

 

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