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      OmicStudio: A composable bioinformatics cloud platform with real‐time feedback that can generate high‐quality graphs for publication

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          Abstract

          OmicStudio focuses on speed, quality together with flexibility. Generally, OmicStudio can not only meet the users' demand of ordinary bioinformatics data analysis, statistics, and visualization, but also provides them freedom of data mining beyond developer's framework. Additionally, unlimited to developer's aesthetics, users can get more elegant graphs through customizing. Available online https://www.omicstudio.cn.

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          Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

          Evan Bolyen, Jai Rideout, Matthew Dillon … (2019)
          Article 0 comments Cited 5753 times – based on 0 reviews     Review now
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            antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline

            Kai Blin, Simon Shaw, Katharina Steinke … (2019)
            Abstract Secondary metabolites produced by bacteria and fungi are an important source of antimicrobials and other bioactive compounds. In recent years, genome mining has seen broad applications in identifying and characterizing new compounds as well as in metabolic engineering. Since 2011, the ‘antibiotics and secondary metabolite analysis shell—antiSMASH’ (https://antismash.secondarymetabolites.org) has assisted researchers in this, both as a web server and a standalone tool. It has established itself as the most widely used tool for identifying and analysing biosynthetic gene clusters (BGCs) in bacterial and fungal genome sequences. Here, we present an entirely redesigned and extended version 5 of antiSMASH. antiSMASH 5 adds detection rules for clusters encoding the biosynthesis of acyl-amino acids, β-lactones, fungal RiPPs, RaS-RiPPs, polybrominated diphenyl ethers, C-nucleosides, PPY-like ketones and lipolanthines. For type II polyketide synthase-encoding gene clusters, antiSMASH 5 now offers more detailed predictions. The HTML output visualization has been redesigned to improve the navigation and visual representation of annotations. We have again improved the runtime of analysis steps, making it possible to deliver comprehensive annotations for bacterial genomes within a few minutes. A new output file in the standard JavaScript object notation (JSON) format is aimed at downstream tools that process antiSMASH results programmatically.
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              Snakemake--a scalable bioinformatics workflow engine.

              Johannes Köster, Sven Rahmann (2012)
              Snakemake is a workflow engine that provides a readable Python-based workflow definition language and a powerful execution environment that scales from single-core workstations to compute clusters without modifying the workflow. It is the first system to support the use of automatically inferred multiple named wildcards (or variables) in input and output filenames. http://snakemake.googlecode.com. johannes.koester@uni-due.de.
              Article 0 comments Cited 713 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Fengye Lyu: fylv@lc-bio.com
                Chao Fang: cfang@lc-bio.com
                Journal
                Journal ID (nlm-ta): Imeta
                Journal ID (iso-abbrev): Imeta
                Journal ID (doi): 10.1002/(ISSN)2770-596X
                Journal ID (publisher-id): IMT2
                Title: iMeta
                Publisher: John Wiley and Sons Inc. (Hoboken )
                ISSN (Print): 2770-5986
                ISSN (Electronic): 2770-596X
                Publication date (Electronic): 06 February 2023
                Publication date Collection: February 2023
                Volume: 2
                Issue: 1 ( doiID: 10.1002/imt2.v2.1 )
                Electronic Location Identifier: e85
                Affiliations
                [ 1 ] Operation Department LC‐Bio Technology Co., Ltd. Hangzhou China
                Author notes
                [*] [* ] Correspondence: Fengye Lyu and Chao Fang, LC‐Bio Technology Co., Ltd., Hangzhou, China.

                Email: fylv@ 123456lc-bio.com and cfang@ 123456lc-bio.com

                Article
                Publisher ID: IMT285
                DOI: 10.1002/imt2.85
                PMC ID: 10989813
                PubMed ID: 38868333
                SO-VID: c79fcda7-eb09-47e8-8c8b-7071fae4322a
                Copyright © © 2023 LC‐Bio. iMeta published by John Wiley & Sons Australia, Ltd on behalf of iMeta Science.
                License:

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                Date revision received : 06 January 2023
                Date received : 12 August 2022
                Date accepted : 12 January 2023
                Page count
                Figures: 4, Tables: 0, Pages: 6, Words: 3016
                Categories
                Subject: Commentary
                Subject: Commentary
                Custom metadata
                source-schema-version-number 2.0
                cover-date February 2023
                details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.0 mode:remove_FC converted:25.03.2024

                Data availability:

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