ArticleComputing in science & engineering
A PyMOL snippet library for Jupyter to boost researcher productivity.
Article in Computing in science & engineering. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Diterpenes/Diterpenoids and Their Derivatives as Potential Bioactive Leads against Dengue Virus: A Computational and Network Pharmacology Study.Molecules (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Snippets - code templates one line or longer - boost researcher productivity because they are faster to insert than writing the code from scratch and because they reduce debugging time. Several extensions support the use of snippets in Jupyter. We developed a Python version of the pymolsnips library and customized it for use in the jupyterlab-snippets-multimenus extension for JupyterLab. The extension provides access to the snippets by pull-down menus. Each snippet performs one task. Each task often requires many lines of code. This library's availability in Jupyter enables PyMOL users to run PyMOL efficiently inside Jupyter while storing the code and the associated molecular graphics images next to each other in one notebook document. This proximity of code and images supports reproducible research in structural biology, and the use of one computer file facilitates collaborations.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.