Open ramess101 opened 5 years ago
My vote is
A histogram-free reweighting approach to estimate vapor-liquid coexistence properties for non-simulated force fields
Potoff Group - ChE Dept - Wayne State Univ. E: m.soroush@wayne.edu C: 313.980.8605 W: 313.577.3758 HTTP://gomc.eng.wayne.edu
From: Richard Messerly notifications@github.com Sent: Monday, December 10, 2018 3:39 PM To: ramess101/JCED_FOMMS_Manuscript Cc: Mohammad Soroush Barhaghi; Mention Subject: [ramess101/JCED_FOMMS_Manuscript] Title (#7)
@mrshirtshttps://github.com/mrshirts @jpotoffhttps://github.com/jpotoff @msoroushhttps://github.com/msoroush
I have thrown out a lot of different titles for the manuscript (although although most of them are pretty similar). I would appreciate if we could each vote on our favorite title and/or propose new ones.
Here are the top ones so far:
Histogram-free reweighting to estimate vapor-liquid coexistence properties of non-simulated force fields Using histogram-free reweighting to estimate vapor-liquid coexistence properties of non-simulated force fields Histogram-free reweighting enables the estimation of vapor-liquid coexistence properties for non-simulated force fields A histogram-free reweighting approach to estimate vapor-liquid coexistence properties for non-simulated force fields A histogram-free reweighting approach for estimating vapor-liquid coexistence properties of non-simulated force fields Estimating vapor-liquid coexistence properties of non-simulated force fields with histogram-free reweighting
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Does JCED have any rules about titles not starting with articles?
@mrshirts
Not sure. This is all it says on Author Guidelines, "Use a specific rather than a general title. The title should be as brief and informative as possible." But scanning through published JCED articles, I did not see a single manuscript with a title that started with an article. So maybe we should avoid it.
To modify the one @msoroush voted for we could say:
Histogram-free reweighting as an approach to estimate vapor-liquid coexistence properties for non-simulated force fields
@ramess101 @msoroush trying to come up with something better that "non-simulated"...
@jpotoff
Yeah, I don't love that either. I tried "multiple", but then it sounds like Hamiltonian scaling.
@ramess101 @msoroush Not sure about this one, but it's another idea.
Histogram-free prediction of vapor-liquid coexistence properties for a range of force field parameters from the simulation of a single parameter set.
@jpotoff
That is certainly a more informative title, although I think it violates the other JCED suggestion that titles be brief.
Also, one of the NIST reviewers argued that we should not use the term "prediction" when referring to MBAR, since it is really just a post-processing approach that calculates vapor-liquid coexistence values from simulation results. I can see both sides of the argument though.
@ramess101 Another attempt: histogram-free calculation of vapor-liquid equilibria from Grand canonical Monte Carlo simulations.
Histogram-free estimation of multiple vapor-liquid equilibria using Grand Canonical Monte Carlo Simulations and reweighting?
Estimation (or Calculation) of multiple vapor-liquid equilibria using Grand canonical Monte Carlo simulations and histogram-free reweighting?
@ramess101 I think you've got a winner with the last one. I prefer "calculation" over "estimation", though.
@jpotoff Glad you like it, but I am still not satisfied. What about:
Vapor-liquid equilibria (or coexistence) calculations of multiple force fields (or potentials, Hamiltonians, potential models) using Grand canonical Monte Carlo simulations and histogram-free reweighting
@jpotoff @mrshirts @msoroush
Is it important that the title mention Grand canonical Monte Carlo?
Some other ideas:
Histogram-free reweighting: A tool to enable post-simulation force field parameterization
Histogram-free reweighting: A tool to calculate vapor-liquid equilibria post-simulation for multiple force fields
@ramess101 How about this one? I have a preference for "method" over "tool" because to me a "tool" implies a software product, and we're not writing a software paper.
Histogram-free reweighting: A method enabling post-simulation force field optimization.
@jpotoff I have no preference towards tool over method.
I like what you have, but I think we could rearrange it a little more to get:
Histogram-free reweighting: A post-simulation force field optimization method (approach)
@mrshirts @msoroush What are your feelings on the last few titles?
Also, @jpotoff any reason to use optimization over parameterization? Just curious because I go back and forth on these two a lot. To me, optimization implies that these are truly the optimal force field parameters (when they are probably near-optimal at best) while parameterization simply means that we are assigning parameters (could be without a scoring function altogether). So I feel like parameterization is a more conservative word but it could also sell MBAR short because even a random number generator could parameterize a force field (although it certainly would not optimize the force field). Anyways, I am being fairly pedantic here.
@jpotoff @mrshirts @msoroush Any of these titles look good or spark some ideas?
Post-simulation force field optimization to vapor-liquid equilibria with histogram-free reweighting
Post-simulation force field optimization with histogram-free reweighting vapor-liquid coexistence calculations
Post-simulation force field optimization with histogram-free Grand canonical Monte Carlo vapor-liquid coexistence calculations
@ramess101 I like the word "optimization" because with this method we can say definitively that one is not going to find a better set of parameters for the Mie/LJ potential. That's what you're showing with the heat maps. I'm ok with "parameterization" though if you think "optimization" is too strong, though.
Another version of words with friends: Histogram-free reweighting: A post-simulation approach for force field optimization (parameterization)
=> my thought is this is probably the shortest descriptive title we can come up with. We can leave out grand canonical Monte Carlo because even though that is the simulation method we are using, one could apply this method to other types of simulation, as you've done with ITIC and molecular dynamics.
The other one I like is this one: Calculation of multiple vapor-liquid equilibria using Grand canonical Monte Carlo simulations and histogram-free reweighting
@jpotoff
OK, I like the first one (although I don't like having "for force", just doesn't pass the ear test). So I would vote for this name:
Histogram-free reweighting: A post-simulation approach to force field optimization
@mrshirts @msoroush opinions?
I like it. With minor modification:
Histogram-free reweighting: A post-simulation approach to optimize force field
Sincerely, Mohammad
On Dec 12, 2018, at 8:26 PM, Richard Messerly notifications@github.com wrote:
Histogram-free reweighting: A post-simulation approach to force field optimization
@msoroush @ramess101 one more tweak:
Histogram-free reweighting: A post-simulation approach to optimize force field parameters Or the more wordy: Histogram-free reweighting: A post-simulation approach for the optimization of force field parameters
This one is also pretty good: Histogram-free reweighting: A post-simulation approach to force field optimization
@msoroush @jpotoff
I think we are almost there. We could run with about any of those, but I was wondering, do we want to make it clear that these are non-bonded parameters? E.g.,
Histogram-free reweighting: A post-simulation approach to optimize non-bonded (intermolecular) parameters
Histogram-free reweighting: A post-simulation approach to optimize non-bonded parameters
I'm good with this one. I can see the importance of clarifying non-bonded parameters, since we are not parameterizing the complete for field (bond, angles, torsions).
@jpotoff @msoroush
Yeah, I think that could be important. I guess the only thing that is lost here that could be important is the notion of phase equilibria. Is there a good way to include that in the title?
Histogram-free reweighting: A post-simulation approach to optimize non-bonded parameters with multiple (rapid) vapor-liquid coexistence (equilibria) calculations
I like it: A post-simulation approach to optimize non-bonded parameters with rapid vapor-liquid equilibria calculations
@jpotoff @msoroush
I know this approach could be applied to other force fields, but we could also promote the MiPPE force field effectively through the title which would cover both the non-bondeds and VLE:
Histogram-free reweighting: A post-simulation approach to optimize Mie potentials for phase equilibria
Histogram-free reweighting: A post-simulation approach to optimize Mie potentials for phase equilibria
You have my vote!
Chiming in finally after a busy day: histogram-free reweighting to optimize potentials has been done a number of times by us (using MBAR - see Naden et al, and Rich's last two papers), and by others, using single exponential reweighting. The previous title can be read to be describing something potentially novel. However, it has NOT been done with Gibbs Ensemble MC, which are very useful for phase equilibria. So that's probably one of the key parts - that's the real novelty. And the method would work just as well with other potentials besides Mie, so I think that's less important to emphasize - it just happens to be applied with Mie.
So I would propose:
Histogram-free reweighting with Gibbs ensemble Monte Carlo: A post-simulation approach to optimize potentials for phase equilibria
Of course, now it sounds like a JCTC paper, so we'll see if they are OK with it . . .
@mrshirts @jpotoff @msoroush
I agree with Michael that somewhere along the way we lost the novelty of this paper, namely, applying MBAR to GCMC. So I like Michael's title, after correcting GEMC to GCMC :-)
Histogram-free reweighting with Grand canonical Monte Carlo: A post-simulation approach to optimize non-bonded potentials for phase equilibria
Not exactly succinct though
Hah, sorry. Wrong ensemble :) Too focused on writing a final.
@jpotoff @mrshirts @msoroush
Here are the JCED requirements that are specific to molecular modeling simulation studies:
Should we mention cyclohexane specifically since we have new parameters/data?
@ramess101 We studied many compounds, branched alkane, alkyne, and cyclohexane. I think it is better to not mentioning cyclohexane.
@msoroush
True. I agree that we dont want to list all the different compounds, especially if our title is referring more to the method than the force field and the data.
However, we only apply the post-simulation optimization to cyclohexane. So we only have new MiPPE parameters for cyclohexane. Although you could argue that epsilon scaling produced new parameters, we never really report those. And we only really have “new” data for cyclohexane, since the other data were more for validation.
I guess I just don’t want the MiPPE cyclohexane parameters to be lost if someone is searching for them. Having this in the title would make sure people see this as part of the MiPPE series.
@jpotoff @mrshirts
What do you think about this title?
Histogram-free reweighting with Grand canonical Monte Carlo: A post-simulation optimization of the cyclohexane Mie potential for phase equilibria
On Thursday, December 13, 2018, Mohammad Soroush Barhaghi < notifications@github.com> wrote:
@ramess101 https://github.com/ramess101 We studied many compounds, branched alkane, alkyne, and cyclohexane. I think it is better to not mentioning cyclohexane.
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@ramess101 Trying another way: Mie Potentials for Phase Equilibria: Parameterization of cyclohexane using histogram-free reweighting grand canonical Monte Carlo simulations .
@jpotoff I think you are right that this would be a better title if we are including cyclohexane in the title. So the guess is do we want to have the parameterization of cyclohexane as the focus? I need to think about this one for a while.
The manuscript grew out of the realization that MBAR could do what HR does and more. But we never intended for this to be one of the canonical MiPPE publications.
On Thursday, December 13, 2018, Jeffrey Potoff notifications@github.com wrote:
@ramess101 https://github.com/ramess101 Trying another way: Mie Potentials for Phase Equilibria: Parameterization of cyclohexane using histogram-free reweighting grand canonical Monte Carlo simulations .
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@ramess101 I'm ok with leaving cyclohexane out and shrinking the title. I'm just wordsmithing on some of the ideas that are being posted.
@jpotoff
I appreciate it. All ideas are welcome. I am not opposed to this morphing into a MiPPE paper, I just didnt write it with that in mind. I think the cyclohexane parameterization is certainly the show pony for this manuscript, so thats why I kind of wanted it mentioned in the title. But I dont want that the overshadow the methodology that is the novel aspect.
On Thursday, December 13, 2018, Jeffrey Potoff notifications@github.com wrote:
@ramess101 https://github.com/ramess101 I'm ok with leaving cyclohexane out and shrinking the title. I'm just wordsmithing on some of the ideas that are being posted.
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But I don't want that the overshadow the methodology that is the novel aspect.
Yeah, I'd agree on this.
Problem with "Histogram-free reweighting with Grand canonical Monte Carlo: A post-simulation optimization of the cyclohexane Mie potential for phase equilibria" is that it implies that it's only for cyclohexane Mie potential.
So I'd still go with "Histogram-free reweighting with Gibbs ensemble Monte Carlo: A post-simulation approach to optimize potentials for phase equilibria", and emphasize in the abstract that it's demonstrated with cyclohexane in in the Mie potential.
@mrshirts @ramess101: "Histogram-free reweighting with grand canonical Monte Carlo: A post-simulation approach to optimize non-bonded potentials for phase equilibria." Good enough?
@jpotoff @mrshirts
Yeah I think this is the best title: it focuses on GCMC-MBAR and it does not limit the method to just Mie potentials or just cyclohexane.
One small question that JCED might end up dictating anyways, should the capitalization of GCMC be "Grand canonical Monte Carlo", "grand canonical Monte Carlo" or "Grand Canonical Monte Carlo"?
Typically only "Monte Carlo" is capitalized.
@jpotoff @mrshirts
Sorry for my obsession with the title, but I was thinking about how to make it a little more succinct. What do you think about eliminating “a” and “approach”:
Histogram-free reweighting with grand canonical Monte Carlo: Post-simulation optimization of non-bonded potentials for phase equilibria
On Friday, December 14, 2018, Jeffrey Potoff notifications@github.com wrote:
Typically only "Monte Carlo" is capitalized.
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Titles are important (My greatest creative achievement is probably the Science perspective article title on Folding@Home - "Screensavers of the world, unite!").
I think that latest title is works well.
@mrshirts
Haha, that is an amazing title! I dont think I’m aiming for that level of creativity...maybe in our next publication together.
@jpotoff Any objections to the latest title proposal?
On Saturday, December 15, 2018, Michael Shirts notifications@github.com wrote:
Titles are important (My greatest creative achievement is probably the Science perspective article title on Folding@Home - "Screensavers of the world, unite!").
I think that latest title is works well.
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@ramess101 @mrshirts
Histogram-free reweighting with grand canonical Monte Carlo: Post-simulation optimization of non-bonded potentials for phase equilibria
I'm good with this.
@jpotoff @mrshirts
OK, I think we finally have a winner
@mrshirts @jpotoff @msoroush
I have thrown out a lot of different titles for the manuscript (although although most of them are pretty similar). I would appreciate if we could each vote on our favorite title and/or propose new ones.
Here are the top ones so far:
Histogram-free reweighting to estimate vapor-liquid coexistence properties of non-simulated force fields Using histogram-free reweighting to estimate vapor-liquid coexistence properties of non-simulated force fields Histogram-free reweighting enables the estimation of vapor-liquid coexistence properties for non-simulated force fields A histogram-free reweighting approach to estimate vapor-liquid coexistence properties for non-simulated force fields A histogram-free reweighting approach for estimating vapor-liquid coexistence properties of non-simulated force fields Estimating vapor-liquid coexistence properties of non-simulated force fields with histogram-free reweighting