Package: phages2050
"Keep calm, use AI for phages and stop AMR"PHAGES2050 is a novelPython 3.8+ programming languageframework to boost bacteriophage research & therapy and infrastructure in order to achieve the full potential to fight against antimicrobial resistant bacteria withinNatural Language Processing (NLP)andDeep Learning.Our project is about developing a AI-based framework for microbiologists and bioinformaticians who hunt, explore and classify phages. Applying the framework will shorten the duration of computational methods required to match phages with bacteria for specific patient cases. Having such organised framework at hand and freely-available will help develop personalized phage therapy and make it accessible to people worldwide.Watch thePHAVES #3talk to learn more.Table of ContentsFramework modules|Usage|Documentation|Installation|Community and Contributions|Have a question?|Found a bug?|Team|Change log|Code of Conduct|LicenseFramework modulescrawlers- set of functions responsible for bacteriophages data scraping from different sources (MillardLab, NCBI)features- set of functions responsible for nucleotides and proteins feature extraction for Machine Learning classification and deeper analysisembeddings- set of pre-trained Embedding models for nucleotides and proteins vectorizationclassifiers- set of pre-trained Machine Learning models dedicated for bacteriophage researchexplore- set of data visualization techniques in 2D or 3D dedicated for deeper bacteriophages explorationUsageThe repository includes numerous examples of using the framework in Jupyter Notebook format (*.ipynb). The most expected ones by the community are listed below:CrawlersMillardLab bacteriophage crawlerNCBI bacteriophages crawlers (planned):taxonomy, host and other expected meta-data;complete genome sequences in FASTA format;set of genes and proteins in FASTA format;EmbeddingsBacteriophage proteins embeddingBacteriophage DNA embeddingBacteriophage sequence-based biological and biochemical features extraction (planned)ClassifiersBacteriophage structural protein classifier with 95% of accuracyBacteriophage lifecycle classifier including chronic infection (planned)Bacteriophage taxonomy classifier (planned)Bacteriophage prophage detector and extractor (planned)Lysis zones multi-level-classification (in progress)ExploreBacteriophages in 3D space based on:DNA embedding (planned)proteins embedding (planned)biological and biochemical features (planned)custom user features (planned)DocumentationThe official documentation is hosted on ReadTheDocs:https://phages2050.readthedocs.ioInstallationPHAGES2050can be installed by running:pip install phages2050It requires Python 3.8.0+ to run. You can also use Conda:conda install -c conda-forge phages2050Install from GitHubIf you can't wait for the latest hotness and want to install from GitHub, use:pip install git+git://github.com/ptynecki/PHAGES2050Proteins' embeddingIf you want to use Bacteriophage proteins vectorizers then remember to install extra package for proteins embedding:pip install -U "bio-embeddings[all] @ git+https://github.com/sacdallago/bio_embeddings.git"
pip install git+https://github.com/facebookresearch/esm.gitCommunity and ContributionsHappy to see you willing to make the PHAGES2050 better. Development on the latest stable version of Python 3+ is preferred. As of this writing it's 3.8. You can use any operating system.If you're fixing a bug or adding a new feature, add a test withpytestand check the code withBlackandmypy. Before adding any large feature, first open an issue for us to discuss the idea with the core devs and community.Have a question?Obviously if you have a private question or want to cooperate with us, you can always reach out to us directly via ourPhage Directory Slack(channel#PHAGES2050).Found a bug?Feel free to add a new issue with a respective title and description on thethe PHAGES2050 repository. If you already found a solution to your problem, we would be happy to review your pull request.TeamCore Developers, Domain Experts, Community Managers and Educators who contributing to PHAGES2050:Piotr TyneckiYana MininaIwona ŚwiętochowskaPrzemysław MituraJoanna KazimierczakArkadiusz GuzińskiBogusław ZimnochJessica Sacher, PhDShawna McCallin, PhDMarie-Agnes Petit, PhDJan ZhengChange logThe log's will become rather long. It moved to its own file.SeeCHANGELOG.md.Code of ConductEveryone interacting in the PHAGES2050 project's development, issue trackers and Slack discussion is expected to follow theCode of Conduct.LicenseThe PHAGES2050 package and pre-trained models are released under the under terms ofthe MIT License.