kandi X-RAY | OpenWorm Summary
kandi X-RAY | OpenWorm Summary
OpenWorm aims to build the first comprehensive computational model of Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well-studied in biology, a deep, principled understanding of the biology of this organism remains elusive. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so, we are incorporating the data available from the scientific community into software models. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps. You can earn a badge with us simply by trying out this package! Click on the image below to get started.
Top functions reviewed by kandi - BETA
- Executes the given command and returns the result .
OpenWorm Key Features
OpenWorm Examples and Code Snippets
void FloydWarshall(MeshGraph * pMesh, Array2D& M) void computeSkeleton(t3DModel *pModel, int sourcePointID, SN::SkeletonNode * skeleton, int * ite, bool &
# generate 2 neurons & 1 muscle with current inputs using parameter set A pynml examples/LEMS_c302_A_IClamp.xml # generate full scale network using parameter set C pynml examples/LEMS_c302_C_Full.xml # generate pharynge
INSTALLDIR=~/git mkdir $INSTALLDIR cd $INSTALLDIR git clone https://github.com/openworm/muscle_model pip install lxml git clone https://github.com/NeuralEnsemble/libNeuroML.git cd libNeuroML git checkout development python setup.py install cd .. gi
Trending Discussions on Genomics
I´m working with two text files that look like this: File 1...
ANSWERAnswered 2022-Apr-09 at 00:49
Perhaps you are after this?
I'm using the software plink2 (https://www.cog-genomics.org/plink/2.0/) and I'm trying to iterate over 3 variables.
This software admits an input file with .ped extention file and an exclude file with .txt extention which contains a list of names to be excluded from the input file.
The idea is to iterate over the input files and then over exclude files to generate single outputfiles.
- Input files: Highland.ped - Midland.ped - Lowland.ped
- Exclude-map files: HighlandMidland.txt - HighlandLowland.txt - MidlandLowland.txt
- Output files: HighlandMidland - HighlandLowland - MidlandHighland - MidlandLowland - LowlandHighland - LowlandMidland
The general code is:...
ANSWERAnswered 2021-Dec-09 at 23:50
Honestly, I think your current code is quite clear; but if you really want to write this as a loop, here's one possibility:
I am making a code which takes in jumble word and returns a unjumbled word , the data.json contains a list and here take a word one-by-one and check if it contains all the characters of the word and later checking if the length is same , but the problem is when i enter a word as helol then the l is checked twice and giving me some other outputs including the main one(hello). i know why does it happen but i cant get a fix to it...
ANSWERAnswered 2021-Nov-25 at 18:33
As I understand it you are trying to identify all possible matches for the jumbled string in your list. You could sort the letters in the jumbled word and match the resulting list against sorted lists of the words in your data file.
I am trying to use plink1.9 to split multiallelic into biallelic. The input is that...
ANSWERAnswered 2021-Nov-17 at 09:45
I used bcftools to complete the task.
I have a FASTA file that has about 300000 sequences but some of the sequences are like these...
ANSWERAnswered 2021-Oct-12 at 20:28
You can match your non-X containing FASTA entries with the regex
>.+\n[^X]+\n. This checks for a substring starting with
> having a first line of anything (the FASTA header), which is followed by characters not containing an X until you reach a line break.
For example, I have two strings:...
ANSWERAnswered 2021-Oct-04 at 22:27
For your example your pattern would be:
I am currently trying to run genomic analyses pipelines using Hail(library for genomics analyses written in python and Scala). Recently, Apache Spark 3 was released and it supported GPU usage.
I tried spark-rapids library start an on-premise slurm cluster with gpu nodes. I was able to initialise the cluster. However, when I tried running hail tasks, the executors keep getting killed.
On querying in Hail forum, I got the response that
That’s a GPU code generator for Spark-SQL, and Hail doesn’t use any Spark-SQL interfaces, only the RDD interfaces.
So, does Spark3 not support GPU usage for RDD interfaces?...
ANSWERAnswered 2021-Sep-23 at 05:53
As of now, spark-rapids doesn't support GPU usage for RDD interfaces.
Apache Spark 3.0+ lets users provide a plugin that can replace the backend for SQL and DataFrame operations. This requires no API changes from the user. The plugin will replace SQL operations it supports with GPU accelerated versions. If an operation is not supported it will fall back to using the Spark CPU version. Note that the plugin cannot accelerate operations that manipulate RDDs directly.
Here, an answer from spark-rapids team
We do not support running the RDD API on GPUs at this time. We only support the SQL/Dataframe API, and even then only a subset of the operators. This is because we are translating individual Catalyst operators into GPU enabled equivalent operators. I would love to be able to support the RDD API, but that would require us to be able to take arbitrary java, scala, and python code and run it on the GPU. We are investigating ways to try to accomplish some of this, but right now it is very difficult to do. That is especially true for libraries like Hail, which use python as an API, but the data analysis is done in C/C++.
I have 1500 files with the same format (the .scount file format from PLINK2 https://www.cog-genomics.org/plink/2.0/formats#scount), an example is below:...
ANSWERAnswered 2021-Sep-07 at 11:10
I have been implementing a suite of RecordBatchReaders for a genomics toolset. The standard unit of work is a RecordBatch. I ended up implementing a lot of my own compression and IO tools instead of using the existing utilities in the arrow cpp platform because I was confused about them. Are there any clear examples of using the existing compression and file IO utilities to simply get a file stream that inflates standard zlib data? Also, an object diagram for the cpp platform would be helpful in ramping up....
ANSWERAnswered 2021-Jun-02 at 18:58
Here is an example program that inflates a compressed zlib file and reads it as CSV.
No vulnerabilities reported
Run our nervous system model, known as c302, on your computer.
In parallel, run our 3D worm body model, known as Sibernetic, on your computer, using the output of the nervous system model.
Produce graphs from the nervous system and body model that demonstrate its behavior on your computer for you to inspect.
Produce a movie showing the output of the body model.
You should have at least 60 GB of free space on your machine and at least 2GB of RAM
You should be able to clone git repositories on your machine. Install git, or this GUI may be useful.
Install Docker on your system.
If your system does not have enough free space, you can use an external hard disk. On MacOS X, the location for image storage can be specified in the Advanced Tab in Preferences. See this thread in addition for Linux instructions.
Ensure the Docker daemon is running in the background (on MacOS/Windows there should be an icon with the Docker whale logo showing in the menu bar/system tray).
Open a terminal and run: git clone http://github.com/openworm/openworm; cd openworm
Optional: Run ./build.sh (or build.cmd on Windows). If you skip this step, it will download the latest released Docker image from the OpenWorm Docker hub.
Run ./run.sh (or run.cmd on Windows).
About 5-10 minutes of output will display on the screen as the steps run.
The simulation will end. Run stop.sh (stop.cmd on Windows) on your system to clean up the running container.
Inspect the output in the output directory on your local machine.
-d [num] : Use to modify the duration of the simulation in milliseconds. Default is 15. Use 5000 to run for time to make the full movie above (i.e. 5 seconds).
Open a terminal and run ./run-shell-only.sh (or run-shell-only.cmd on Windows). This will let you log into the container before it has run master_openworm.py. From here you can inspect the internals of the various checked out code bases and installed systems and modify things. Afterwards you'll still need to run ./stop.sh to clean up.
If you wish to modify what gets installed, you should modify Dockerfile. If you want to modify what runs, you should modify master_openworm.py. Either way you will need to run build.sh in order to rebuild the image locally. Afterwards you can run normally.
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