Hi,
You still should look at micrographs from all defocus ranges
when you optimise autopicking parameters (threshold etc).
Best regards,
Takanori Nakane
On 2019/11/01 5:57, Dieter Blaas wrote:
> Hi,
>
> does this mean that, if I already have a 3D map (from this very data
> set) and use it as a template for a second round of autopicking, I do
> not have to care about the below?
>
> bw Dieter
>
> ------------------------------------------------------------------------
> Dieter Blaas,
> Max F. Perutz Laboratories
> Medical University of Vienna,
> Inst. Med. Biochem., Vienna Biocenter (VBC),
> Dr. Bohr Gasse 9/3,
> A-1030 Vienna, Austria,
> Tel: 0043 1 4277 61630,
> Fax: 0043 1 4277 9616,
> e-mail: [log in to unmask]
> ------------------------------------------------------------------------
>
> Am 31.10.2019 um 17:22 schrieb Takanori Nakane:
>> Hi,
>>
>> You are correct, if you perform Class2D on your manually
>> picked particles and generate templates for autopicking.
>> However, you should look at micrographs from all defocus ranges
>> when you optimise autopicking parameters (threshold etc).
>>
>> If you use your manually picked particles to train
>> other programs (e.g. neural-network based pickers),
>> you might need to train on low-defocus micrographs as well.
>> This depends on the program.
>>
>> Best regards,
>>
>> Takanori Nakane
>>
>>> Dear all,
>>>
>>> maybe this is a silly question but I thought I ask anyway.
>>> When I'm picking particles manually, does it matter if I pick particles
>>> accross all defocus values, or is it ok to stay on larger defocus values
>>> where particle are more identifiable?
>>> I was thinking that since we strongly low pass filter our 2D classes, it
>>> is ok to stick with larger defocus values. Am I correct?
>>>
>>> Thank you for your input.
>>> Vincent
>>>
>>> --
>>>
>>> Vincent Chaptal, PhD
>>>
>>> MMSB -UMR5086
>>>
>>> Drug Resistance and Membrane Proteins Laboratory
>>>
>>> 7 passage du Vercors
>>>
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>>>
>>> FRANCE
>>>
>>> +33 4 37 65 29 01
>>>
>>> http://mmsb.cnrs.fr/en/
>>>
>>>
>>>
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