Saravanan666/pypi-org huggingface dataset:
Package: biosteam
Read in:EspañolContentsWorkshopsWhat is BioSTEAM?InstallationDocumentationBug reportsContributingLicense informationAbout the authorsReferencesWorkshopsJoin us on Friday, Jan 20, 9:15-10:15am CST, for a BioSTEAM workshop!
Emailbiosteamdevelopmentgroup@gmail.comfor details.What is BioSTEAM?BioSTEAM is a fast and flexible package for the design, simulation,
techno-economic analysis, and life cycle assessment of biorefineries under uncertainty[1].
BioSTEAM is built to streamline and automate early-stage technology evaluations
and to enable rigorous sensitivity and uncertainty analyses. Complete
biorefinery configurations are available at theBioindustrial-ParkGitHub repository,
BioSTEAM’s premier repository for biorefinery models and results. The long-term
growth and maintenance of BioSTEAM is supported through both community-led
development and the research institutions invested in BioSTEAM, including theCenter for Advanced Bioenergy and Bioproducts Innovations (CABBI).
Through its open-source and community-lead platform, BioSTEAM aims to foster
communication and transparency within the biorefinery research community for an
integrated effort to expedite the evaluation of candidate biofuels and
bioproducts.Data on chemicals and algorithms to estimate thermodynamic properties are
imported fromchemicalsandthermo,
community-driven open-source libraries developed by Caleb Bell. BioSTEAM’s
premire thermodynamic engine,ThermoSTEAM,
builds upon these libraries to facilitate the creation of thermodynamic property packages.InstallationGet the latest version of BioSTEAM fromPyPI. If you have an installation of Python with pip, simple install it with:$ pip install biosteamTo get the git version, run:$ git clone git://github.com/BioSTEAMDevelopmentGroup/biosteamFor help on common installation issues, please visit thedocumentation.DocumentationBioSTEAM’s documentation is available on the web:http://biosteam.readthedocs.io/Bug reportsTo report bugs, please use the BioSTEAM’s Bug Tracker at:https://github.com/BioSTEAMDevelopmentGroup/biosteamContributingFor guidelines on how to contribute, visit:https://biosteam.readthedocs.io/en/latest/contributing/index.htmlLicense informationSeeLICENSE.txtfor information on the terms & conditions for usage
of this software, and a DISCLAIMER OF ALL WARRANTIES.Although not required by the BioSTEAM license, if it is convenient for you,
please cite BioSTEAM if used in your work. Please also consider contributing
any changes you make back, and benefit the community.About the authorsBioSTEAM was created and developed byYoel Cortés-Peñaas part of theGuest Groupand theCenter for Advanced Bioenergy and Bioproducts Innovation (CABBI)at theUniversity of Illinois at Urbana-Champaign (UIUC).References[1]Cortés-Peña et al. BioSTEAM: A Fast and Flexible Platform for the Design, Simulation, and Techno-Economic Analysis of Biorefineries under Uncertainty. ACS Sustainable Chem. Eng. 2020..
Package: biosynonyms
BiosynonymsA decentralized database of synonyms for biomedical entities and concepts. This
resource is meant to be complementary to ontologies, databases, and other
controlled vocabularies that provide synonyms. It's released under a permissive
license (CC0), so they can be easily adopted by/contributed back to upstream resources.Here's how to get the data:importbiosynonyms# Uses an internal data structurepositive_synonyms=biosynonyms.get_positive_synonyms()negative_synonyms=biosynonyms.get_negative_synonyms()# Get ready for use in NER with Gilda, only using positive synonymsgilda_terms=biosynonyms.get_gilda_terms()SynonymsThe data are also accessible directly through TSV such that anyone can consume them
from any programming language.Thepositives.tsvhas the following
columns:textthe synonym text itselfcuriethe compact uniform resource identifier (CURIE) for a biomedical
entity or concept, standardized using the Bioregistrynamethe standard name for the conceptscopethe match type, written as a CURIE from
theOBO in OWL (oio)controlled vocabulary,
i.e., one of:oboInOwl:hasExactSynonymoboInOwl:hasNarrowSynonymoboInOwl:hasBroadSynonymoboInOwl:hasRelatedSynonymoboInOwl:hasSynonym(use this if the scope is unknown)typethe synonym property type, written as a CURIE from
theOBO Metadata Ontology (omo)controlled vocabulary,
e.g., one of:OMO:0003000(abbreviation)OMO:0003001(ambiguous synonym)OMO:0003002(dubious synonym)OMO:0003003(layperson synonym)OMO:0003004(plural form)...referencesa comma-delimited list of CURIEs corresponding to publications
that use the given synonym (ideally using highly actionable identifiers from
semantic spaces likepubmed,pmc,doi)contributorthe ORCID identifier of the contributorHere's an example of some rows in the synonyms table (with linkified CURIEs):textcuriescopereferencescontributorPI(3,4,5)P3CHEBI:16618oio:hasExactSynonympubmed:29623928,pubmed:208179570000-0003-4423-4370phosphatidylinositol (3,4,5) P3CHEBI:16618oio:hasExactSynonympubmed:296955320000-0003-4423-4370Incorrect SynonymsThenegatives.tsvhas the following
columns for non-trivial examples of text strings that aren't synonyms. This
document doesn't address the same issues as context-based disambiguation, but
rather helps dscribe issues like incorrect sub-string matching:textthe non-synonym text itselfcuriethe compact uniform resource identifier (CURIE) for a biomedical
entity or concept thatdoes notmatch the following text, standardized
using the Bioregistryreferencessame as forpositives.tsv, illustrating documents where this
string appearscontributorthe ORCID identifier of the contributorHere's an example of some rows in the negative synonyms table (with linkified
CURIEs):textcuriereferencescontributorPI(3,4,5)P3hgnc:22979pubmed:29623928,pubmed:208179570000-0003-4423-4370Known LimitationsIt's hard to know which exact matches between different vocabularies could be
used to deduplicate synonyms. Right now, this isn't covered but some partial
solutions already exist that could be adopted.LicenseAll data are available under CC0 license. All code is available under MIT
license.
Package: bioTEA
BioTEA, where Tea is short for Transcript Enrichment Analysis, is a pipeline for Differential Gene expression Analysis with microarray and RNA-seq data.
It can download, preprocess and perform DEAs quickly, easily and in a reproducible way from the command line.Check out the BioTEA Docker container, where the analysis code of BioTEA lives!Read the publication:Visentin, L.; Scarpellino, G.; Chinigò, G.; Munaron, L.; Ruffinatti, F.A. BioTEA: Containerized Methods of Analysis for Microarray-Based Transcriptomics Data. Biology 2022, 11, 1346.InstallationIMPORTANT: BioTEA works on UNIX systems. To run on Windows, use theWindows Subsystems for Linux service.InstallDocker. The exact process is specific to your package manager:For Ubuntu,follow this guide from the official Docker documentation.For MacOS,follow this guide from the official Docker documentation.For Arch Linux, install with:pacman-Syudocker
systemctlenable--nowdocker.serviceYou may need administrator privileges.For other distros, check your distro package manager documentation.InstallPythonversion 3.9 or over. Again, this is dependent on your package manager:On Ubuntu, runapt update && apt install python3.9. Depending on when you read this guide, you may need to tap intothe deadsnakes PPA. Read the guides on the link I provided for more information. Just be sure that the result ofpython --versionis3.9or higher when you continue to the following steps.On Arch linux, runpacman -Syu python.On MacOS,follow this guide in the python docs.Optionalbut strongly recommended: Make a Python virtual environment to use bioTEA in. You can search online for a way to do this in your OS.Install bioTEA withpip:pip install biotea.IMPORTANT: Sometimes, critical bugs are fixed on the main branch but are yet to be released to PyPi.
To get the development version of BioTEA, install it withpip install 'biotea @ git+https://github.com/CMA-Lab/bioTEA.git#subdirectory=src/bioTea'.
If you run into problems, try and use this bleeding edge version, your issue might be fixed already!If installed correctly,biotea infoshould give some information on the tool.UsageThe publication provides an overview of the tool and its usage. It is a good place to start. For more information on the various commands, readthe wiki.If you run into problems using the BioTEA CLI, readthe FAQ page on the wiki. If you still cannot solve the issue,file a bug report, detailing as much as you can your problem, including the versions of bioTEA, Python interpreter, Docker engine and your OS.If you think that the issue is coming from the docker container (i.e. the Docker container is correctly launched but the analysis fails), you cancreate an issue in the bioTEA-box repository.ContributingTo learn how you can contribute to the tool,read the CONTRIBUTING guide.Version compatibilityThe BioTEA cli generally gets more frequent updates than the BioTEA box.
This causes their versions to drift apart.
We stride to keep compatibility between the BioTEA cli and the boxwhen the major versions are identical. This means that all BioTEA versionx.y.zcan run any BioTEA box of versionx.*.*.
Package: biothings-explorer
BioThings ExplorerIntroductionThis is the development repo for the python client of BioThings Explorer. This tool aims at helping users querying and linking results from a variety of biomedical relevant APIs through one interface. The project is funded by the NCATS Translator project.P.S. — Documentation is Available at//biothings-explorer.readthedocs.io.Revelant ConceptsBioLink ModelThe BioLink Modeldefines a high level datamodel of biological entities (genes, diseases, phenotypes, pathways, individuals, substances, etc) and their associations. BioThings Explorer restructures outputs from different APIs into the data model defined by BioLink, so that they can be easily connected and queried.SmartAPISmartAPIaims to maximize the FAIRness (Findability, Accessibility, Interoperability, and Reusability) of web-based Application Programming Interfaces (APIs). Rich metadata is essential to properly describe your API so that it becomes discoverable, connected, and reusable. BioThings Explorer takes advantage of the rich metadata information described in SmartAPI and create a meta knowledge graph, allowing BioThings Explorer to autonomously query a distributed knowledge graph. The distributed knowledge graph is made up of biomedical APIs that have been annotated with semantically-precise descriptions of their inputs and outputs.Current Integrated APIsMyGene.info APIMyVariant.info APIMyChem.info APIMyDisease.info APISemmed APIBioLink APIDGIdb APICORD Gene APICORD Protein APICORD Chemical APICORD Cell APICORD Disease APICORD Molecular Activity APICORD Biological Process APICORD Genomic Entity APICORD Anatomy APICORD Cellular Component APIEBIgene2phenotype APIDISEASES APIPFOCR APIQuickGO APILitVar APIOntology Lookup Service APIStanford Biosample APIChEMBL APICTD APIOpenTarget APIRGD APIAutomat CORD19 Scibite APIAutomat CORD19 Scigraph APIAutomat CORD19 Pharos APIAutomat CORD19 hetio APIAutomat CORD19 HMDB APIHow to use the packageOfficial Documentation is Available at//biothings-explorer.readthedocs.ioJupyter notebook demo is located atthis folder.Some real world use cases of BioThings Explorer.Why does imatinib have an effect on the treatment of chronic myelogenous leukemia (CML)?What drugs might be used to treat hyperphenylalaninemia?Finding New Uses for Existing Drugs to Treat Parkinson’s DiseaseFinding Marketed Drugs that Might Treat an Unknown Syndrome by Perturbing the Disease Mechanism Pathway
Package: bioticDETR
bioticDETR - Detection Transformers for Biotic InteractionsOverviewTools to create AI nural network models for biotic interactions.InstallationInstall from the Python Package Index (PyPI):pip install bioticDETRDocumentationhttps://bioticDETR.readthedocs.ioSource Codehttps://github.com/IsotopeC/bioticDETR
Package: biotite
Biotite projectBiotiteis your Swiss army knife for bioinformatics.
Whether you want to identify homologous sequence regions in a protein family
or you would like to find disulfide bonds in a protein structure:Biotitehas the right tool for you.
This package bundles popular tasks in computational molecular biology
into a uniformPythonlibrary.
It can handle a major part of the typical workflow
for sequence and biomolecular structure data:Searching and fetching data from biological databasesReading and writing popular sequence/structure file formatsAnalyzing and editing sequence/structure dataVisualizing sequence/structure dataInterfacing external applications for further analysisBiotiteinternally stores most of the data asNumPyndarrayobjects,
enablingfast C-accelerated analysis,intuitive usability throughNumPy-like indexing syntax,extensibility through direct access of the internalNumPyarrays.As a result the user can skip writing code for basic functionality (like
file parsers) and can focus on what their code makes unique - from
small analysis scripts to entire bioinformatics software packages.If you useBiotitein a scientific publication, please cite:Kunzmann, P. & Hamacher, K. BMC Bioinformatics (2018) 19:346.https://doi.org/10.1186/s12859-018-2367-zInstallationBiotiterequires the following packages:numpyrequestsmsgpacknetworkxSome functions require some extra packages:mdtraj- Required for trajetory file I/O operations.matplotlib- Required for plotting purposes.Biotitecan be installed viaConda…$condainstall-cconda-forgebiotite… orpip$pipinstallbiotiteUsageHere is a small example that downloads two protein sequences from theNCBI Entrezdatabase and aligns them:importbiotite.sequence.alignasalignimportbiotite.sequence.io.fastaasfastaimportbiotite.database.entrezasentrez# Download FASTA file for the sequences of avidin and streptavidinfile_name=entrez.fetch_single_file(uids=["CAC34569","ACL82594"],file_name="sequences.fasta",db_name="protein",ret_type="fasta")# Parse the downloaded FASTA file# and create 'ProteinSequence' objects from itfasta_file=fasta.FastaFile.read(file_name)avidin_seq,streptavidin_seq=fasta.get_sequences(fasta_file).values()# Align sequences using the BLOSUM62 matrix with affine gap penaltymatrix=align.SubstitutionMatrix.std_protein_matrix()alignments=align.align_optimal(avidin_seq,streptavidin_seq,matrix,gap_penalty=(-10,-1),terminal_penalty=False)print(alignments[0])MVHATSPLLLLLLLSLALVAPGLSAR------KCSLTGKWDNDLGSNMTIGAVNSKGEFTGTYTTAV-TA
-------------------DPSKESKAQAAVAEAGITGTWYNQLGSTFIVTA-NPDGSLTGTYESAVGNA

TSNEIKESPLHGTQNTINKRTQPTFGFTVNWKFS----ESTTVFTGQCFIDRNGKEV-LKTMWLLRSSVN
ESRYVLTGRYDSTPATDGSGT--ALGWTVAWKNNYRNAHSATTWSGQYV---GGAEARINTQWLLTSGTT

DIGDDWKATRVGINIFTRLRTQKE---------------------
-AANAWKSTLVGHDTFTKVKPSAASIDAAKKAGVNNGNPLDAVQQMore documentation, including a tutorial, an example gallery and the API
reference is available athttps://www.biotite-python.org/.ContributionInterested in improvingBiotite?
Have a look at thecontribution guidelines.
Feel free to join or community chat onDiscord.
Package: bioto-client
PyClientPython Client for retrieving Bioto sensor dataGoalsSession managementcreate session via device login to get a valid access tokenRetrieving sensor datafind a gardensubscribe to that gardensee subscribtion state for that garden (pending/approved/declined)get an overview of your gardensretrieve sensor data from garden devicesGetting startedThere are two ways of installing this client. The first one using pip:%pipinstall--userbioto-clientThe second option is useful when developing the client. Git clone the project
and usemakefor installation. This will setup avirtual python environmentmanaged viapoetry.%makeinstall
%poetryshellHow to useTipUsebioto-client --helpto see other available commandsStart a user sessionA user session is valid for 24h. When expired you're requested to create a new
session. This can be done as follows:# Call the client with the `user` command to assert a valid session%bioto-clientuser

Loadingsession

Notloggedin,pleasetakethefollowingsteps:1.Onyourcomputerormobiledevicenavigateto:https://biotoco.eu.auth0.com/activate?user_code=NEWT-OKEN2.Enterthefollowingcode:NEWT-OKEN

Succesfullyloggedin.

BiotoCLIclient:1.2.3
Environment:prod
Sessiontoken***5OFd09wFind a gardenGardens can be found by name, the command to do this is:%bioto-clientsearch-garden{name}Subscribe to a gardenTo gain access to the data of this garden you need to subscribe to this garden
using itsID:%bioto-clientsubscribe-garden{garden_id}This will create a subscription request which only the mainter(s) can approve.
To check the state of your subscription see:%bioto-clientsubscriptionsRead device dataReading a device is done bydevice ID, these can be found via the garden
command. Note that a garden might contain multiple devices.To get the latest hourly readings for the last 24h issue the following command:%bioto-clientdevice{device_id}To get these readings for a sepecific date apply a date option. The following
formats are allowed: [%Y-%m-%d | %Y-%m-%dT%H:%M:%S | %H:%M:%S]:%bioto-clientdevice{device_id}--date={date}And to limit or increase the number of hours returned add the hours option:%bioto-clientdevice{device_id}--hours={hours_limit}Improve the clientIf you want to improve the client or add something which you think is missing to
the project you can eitheropen an issueor develop the feature yourself
and opena pull request with your changes.To get started clone this project and create a branch. Now fix the bug or create
the feature you want and write some tests for it to prove it works. This can be
done by executing:%makecheckNoteThis will run both tests and linters, usemake testwhen you're inred - green - refactormodeWhen the checks are all passing, please open aPR
Package: biotoolkit
biotoolkit contains:GCfromDNA.pyGCfromDNA is a python module/command line utility for determining the GC content of DNAsequences, as read from standard fasta (.fa) files.This module formats each sequence name (replacing spaces with underscores), calculates thepercentage GC-content for each sequence, and saves this data as a csv file with a modifiedversion of the original filename (e.g., fasta_file_1.fa --> fasta_file_1_GC.csv).GCfromDNA utilizes parts of the biopython package for analysis. The packagecan be installed with the following command:$ pip install biopythonTo install biotoolkit:$ pip install biotoolkitUpon successful installation, the module can be imported into new python scripts with:from biotoolkit import GCfromDNAFor instance, the following is a complete python script that will invoke the module's functionality:#!/usr/bin/env pythonfrom biotoolkit import GCfromDNAGCfromDNA.compute()It is possible to pass fasta filenames as parameters directly to the compute function.Filenames must be passed to the compute function as a list:GCfromDNA.compute( [file1,file2,file3] )	#if file1 == 'file1.fa', for instanceGCfromDNA can be utilized interactively. From the command line, enter:$ python>>> from biotoolkit import GCfromDNA>>> GCfromDNA.compute()The script can be invoked directly from the directory where it resides.Optional filename arguments must be separated by spaces:$ python GCfromDNA.py file1.fa file2.fa file3.faor alternatively:$ python GCfromDNA.py *.faIf no filename is provided, the program prompts the user to select from fasta files (locatedin the current directory) for processing.
Package: biotools-cli
biotools-cli介绍一个可扩展的，为生物信息学分析提供支持的命令行工具集合（当前仅支持 uniprotkb 网络药理学蛋白质转换基因名）。软件架构软件架构说明安装教程请确保你的计算机已经正确安装了pythonpip install biotools-cli安装 python-Levenshtein 可以加速查找过程（可选）pip install python-Levenshtein使用说明根据你的需求下载uniprotkb数据库文件，一般我们选择 Swiss-Prot 和 Human，格式请选择 xml，如果你下载的是压缩文件，请将它解压。假设最终得到的文件为 uniprot_sprot_human.xml，并把它放置在 example 目录下。从 uniprot_sprot_human.xml 中提取蛋白质名称以及对应的基因名称并保存到 tsv 格式的文本文件中。biotools uniprotkb extract .\example\uniprot_sprot_human.xml .\example\uniprot_sprot_human.xml.tsv如果 xml 文件不变化，extract 命令则仅需要执行一次。准备蛋白质列表，protein.list，参考 .\example\protein.list查找对应的基因名称并保存结果到 .\example\gene.listbiotools uniprotkb lookup .\example\uniprot_sprot_human.xml.tsv .\example\protein.list .\example\gene.list参与贡献Fork 本仓库新建 Feat_xxx 分支提交代码新建 Pull Request特技使用 Readme_XXX.md 来支持不同的语言，例如 Readme_en.md, Readme_zh.mdGitee 官方博客blog.gitee.com你可以https://gitee.com/explore这个地址来了解 Gitee 上的优秀开源项目GVP全称是 Gitee 最有价值开源项目，是综合评定出的优秀开源项目Gitee 官方提供的使用手册https://gitee.com/helpGitee 封面人物是一档用来展示 Gitee 会员风采的栏目https://gitee.com/gitee-stars/
Package: biotop
biotop: picking peaks in physiological dataA simple GUI for human-assisted semiautomatic ECG and respiration preprocessing.PurposeECG analysis of real-world data can be tricky, especially when there are lots of artefacts.
Automated pipelines exist but the results can often not be inspected, and not manually adjusted.The current script allows you to import, view and explore ECG and respiratory data.
You can run automated peak detection which you can then inspect and modify manually.
The results are saved in a JSON file format.PrerequisitesPython 3.XPrerequisite packages are installed automatically using the following:python3 -m pip install biotopUsageFor ECG analysis:biotopFor respiration analysis:respireBasic GUI controlsHold downshiftwhile moving the mouse : Snap to closest maximumMouse scroll wheel up/down : Scroll back and forth in timeCtrlkey + Mouse scroll wheel up/down : Zoom in/out in timeMouse left button double click : Insert peak (or zoom in if not zoomed in enough)Mouse right button single click : Remove peakMouse middle button click : Insert marker for invalid regionMouse middle button double click : Remove invalid regionKeyboard keys:ztoggles between micro and macro zoom (make sure the window has focus)ashows the entire signalLeft/right arrow keys scroll through the signal slowlyPageDown/PageUp keys browse through the signal a full window at a timeDevelopmentInstall latest development version:pip install --upgrade "biotop @ git+https://github.com/florisvanvugt/biotop"WishlistShow a window when waiting for peak autodetection to completeMake sure y axis labels remain visible even for greater zoom
Package: biotranslator
BioTranslator APIBioTranslator is a cross-modal translator which can annotate biology instances only using user-written texts.
The codes here can reproduce the main results in BioTranslator paper, including zero-shot protein function prediction, zero-shot cell type prediction, and predict the nodes and edges of a gene pathway.
BioTranslator takes a user-written textual description of the new discovery and then translates this description to a non-text biological data instance. Our tool frees scientists from limiting their analysis within predefined controlled vocabularies, thus accelerating new biomedical discoveries.For more information, feel free to visit the project's main repositoryhere.
Package: biotree-tools
biotree_toolsCollection of bioinformatics tools related to alignments and phylogenetic treesInstallationconda install -c mmariotti -c bioconda -c etetoolkit  biotree_toolsToolsalignment_toolsutility to manipulate (reformat, subset, trim...) multiple sequence alignmentstree_toolsutility to manipulate (rename, prune, set output...) trees in newick formatphylo_contextgiven protein sequences, build and draw a tree to identify phylogenetic (sub)familiesshow_treeflexible tool to visualize an input protein tree in newick formatRun any tool with option -h to display its usage.