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      • Record: found
      • Abstract: found
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      Two new species of the genus Cheiracanthium C. L. Koch, 1839 (Araneae, Cheiracanthiidae) from China

      research-article
      Author(s): 1 , 1 ,
      Publication date (Electronic):
      Journal: ZooKeys
      Publisher: Pensoft Publishers
      Keywords: COI, description, DNA barcode, long-legged sac spider, taxonomy

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          Abstract

          Two species of the long-legged sac spider genus Cheiracanthium C. L. Koch, 1839 collected from China are diagnosed and described as new to science: Cheiracanthium bannaensis sp. nov. (♂♀) from Yunnan Province and C. bifurcatum sp. nov. (♂♀) from Xinjiang Uyger Autonomous Region. Photos of the habitus and copulatory organs are given. In addition, DNA barcode information of the two new species is provided.

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          Kazutaka Katoh, Daron Standley (2013)
          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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            Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

            Matthew Kearse, Richard Moir, Amy Wilson … (2012)
            Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com
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              MEGA11: Molecular Evolutionary Genetics Analysis Version 11

              Koichiro Tamura, Glen Stecher, Sudhir Kumar (2021)
              The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor , and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net .
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                Author and article information

                Contributors
                Zhaoyi Li:
                ORCID: https://orcid.org/0000-0001-6303-6041
                Role: ConceptualizationRole: Formal analysis
                Feng Zhang:
                ORCID: https://orcid.org/0000-0002-3347-1031
                Role: Formal analysisRole: Funding acquisition
                Journal
                Journal ID (nlm-ta): Zookeys
                Journal ID (iso-abbrev): Zookeys
                Journal ID (publisher-id): 2
                Journal ID (index): urn:lsid:arphahub.com:pub:45048D35-BB1D-5CE8-9668-537E44BD4C7E
                Journal ID (aggregator): urn:lsid:zoobank.org:pub:91BD42D4-90F1-4B45-9350-EEF175B1727A
                Title: ZooKeys
                Publisher: Pensoft Publishers
                ISSN (Print): 1313-2989
                ISSN (Electronic): 1313-2970
                Publication date Collection: 2024
                Publication date (Electronic): 07 May 2024
                Volume: 1200
                Pages: 145-157
                Affiliations
                [1 ] Key Laboratory of Zoological Systematics and Application of Hebei Province, College of Life Sciences, Hebei University, Baoding, Hebei 071002, China Hebei University Baoding China
                [2 ] Hebei Basic Science Center for Biotic Interaction, Hebei University, Baoding, Hebei 071002, China Hebei University Baoding China
                Author notes
                Corresponding author: Feng Zhang ( dudu06042001@ 123456163.com)

                Academic editor: Alireza Zamani

                Author information
                https://orcid.org/0000-0001-6303-6041
                https://orcid.org/0000-0002-3347-1031
                Article
                Publisher ID: 123214
                DOI: 10.3897/zookeys.1200.123214
                PMC ID: 11094398
                PubMed ID: 38751964
                SO-VID: 8b0529ef-a499-4bac-bab0-ae063e08bbd8
                Copyright © Zhaoyi Li, Feng Zhang
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 16 March 2024
                Date accepted : 14 April 2024
                Categories
                Subject: Research Article
                Subject: Araneae
                Subject: Biodiversity & Conservation
                Subject: Species Inventories
                Subject: Cenozoic
                Subject: Neogene
                Subject: Asia

                ScienceOpen disciplines: Animal science & Zoology
                Keywords: coi,description,dna barcode,long-legged sac spider,taxonomy
                Data availability:
                ScienceOpen disciplines: Animal science & Zoology
                Keywords: coi, description, dna barcode, long-legged sac spider, taxonomy

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