<scp>BLOG</scp> 2.0: a software system for character‐based species classification with <scp>DNA</scp> Barcode sequences. What it does, how to use it

Weitschek, Emanuel; Velzen, Robin van; Felici, Giovanni; Bertolazzi, Paola

doi:10.1111/1755-0998.12073

Cited by 75 publications

(76 citation statements)

References 14 publications

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“…It has been handled with several approaches. So far, the following taxonomy of ad-hoc methods has been used [7,8]:…”

Section: Introductionmentioning

confidence: 99%

“…Similarity-based methods (e.g., BLAST [12], NN [13], and TaxonDNA [14]) assign query Barcodes to species based on how much DNA Barcode characters they have in common. Character-based methods (e.g., DNA-BAR [15], BLOG [7], CAOS [16], BRONX [17,18], PTIGS-IdIt [19], Linker [20], Alignment-free analytics [21]) rely on the presence/absence of particular characters in DNA Barcode sequences for identification, instead of using them all [8]. …”

Section: Introductionmentioning

confidence: 99%

“…The DNA Barcode classification problem may be approached as a supervised machine learning problem in the following way [7]: given a reference library composed of DNA Barcode specimen sequences of known species and a collection of unknown DNA Barcode sequences ( query set), recognize the latter into the species that are present in the library.…”

Section: Introductionmentioning

confidence: 99%

“…Subsequently, the classification model can be applied to a query set which contains specimens that require classification. The query set can contain query specimens with unknown species membership or, alternatively, specimens that also have a priori known species membership, allowing verification of the specimen classifications correctness [7]. To obtain reliable results the reference set has to be composed of a sufficient number of specimen sequences for each species (our experiments show that at least 4 specimens per species are necessary to obtain a reliable classification rate), and the sequences of each species have to include possibly all the nucleotide polymorphisms (variations).…”

Section: Introductionmentioning

confidence: 99%

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Supervised DNA Barcodes species classification: analysis, comparisons and results

2014

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BackgroundSpecific fragments, coming from short portions of DNA (e.g., mitochondrial, nuclear, and plastid sequences), have been defined as DNA Barcode and can be used as markers for organisms of the main life kingdoms. Species classification with DNA Barcode sequences has been proven effective on different organisms. Indeed, specific gene regions have been identified as Barcode: COI in animals, rbcL and matK in plants, and ITS in fungi. The classification problem assigns an unknown specimen to a known species by analyzing its Barcode. This task has to be supported with reliable methods and algorithms.MethodsIn this work the efficacy of supervised machine learning methods to classify species with DNA Barcode sequences is shown. The Weka software suite, which includes a collection of supervised classification methods, is adopted to address the task of DNA Barcode analysis. Classifier families are tested on synthetic and empirical datasets belonging to the animal, fungus, and plant kingdoms. In particular, the function-based method Support Vector Machines (SVM), the rule-based RIPPER, the decision tree C4.5, and the Naïve Bayes method are considered. Additionally, the classification results are compared with respect to ad-hoc and well-established DNA Barcode classification methods.ResultsA software that converts the DNA Barcode FASTA sequences to the Weka format is released, to adapt different input formats and to allow the execution of the classification procedure. The analysis of results on synthetic and real datasets shows that SVM and Naïve Bayes outperform on average the other considered classifiers, although they do not provide a human interpretable classification model. Rule-based methods have slightly inferior classification performances, but deliver the species specific positions and nucleotide assignments. On synthetic data the supervised machine learning methods obtain superior classification performances with respect to the traditional DNA Barcode classification methods. On empirical data their classification performances are at a comparable level to the other methods.ConclusionsThe classification analysis shows that supervised machine learning methods are promising candidates for handling with success the DNA Barcoding species classification problem, obtaining excellent performances. To conclude, a powerful tool to perform species identification is now available to the DNA Barcoding community.

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“…It has been handled with several approaches. So far, the following taxonomy of ad-hoc methods has been used [7,8]:…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Supervised DNA Barcodes species classification: analysis, comparisons and results

2014

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“…To test the robustness of our results and clarify ambiguous identifications, we carried out diagnostic character-based identification with program BLOG2.0 (Weitschek et al 2013). Two files in fasta format were prepared: one file consisted of a training set of sequences with species assignments and the other contained a testing set of sequences without species information.…”

Section: Dna Barcoding Identificationmentioning

confidence: 99%

Applying DNA barcoding to conservation practice: a case study of endangered birds and large mammals in China

Li¹,

Cui²,

Juan³

et al. 2016

Biodivers Conserv

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Owning to advantages over traditional species identification methods, DNA barcoding is suggested to be a promising tool in conservation research. However, the use of DNA barcoding to accurately identify unknown samples in conservation practices has not been well documented in the literature. To illustrate this issue, we implemented a survey of endangered birds and mammals in China based on mitochondrial Cytochrome c Oxidase subunit I (COI) gene. We included mostly confiscated specimens and non-invasive samples while concealing species information to simulate real-world scenarios of identification. In total, 47 avian and 39 mammalian specimen were re-identified by sequential analyses of online species assignment, genetic distances, phylogenetic reconstruction, and diagnostic nucleotide method. With this multiple analyses approach, 82 individuals were accurately assigned to the species level and four individuals to the genus level. 78.72% of the avian specimen and 87.18% of mammalian specimen identifications were consistent with morphological classification. Among those inconsistent with morphological classification, we Communicated by Anurag chaurasia.This article belongs to the Topical Collection: Biodiversity protection and reserves.Electronic supplementary material The online version of this article (identified several potential errors including misidentification based on morphology and mislabelling that may have occurred while combining results from different analytical methods. Our case study not only enriches the barcode database, but also reports a successful application of DNA barcoding identification to conservation practices, which could effectively facilitate species identification of unknown samples in conservation practices in the future.

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Identification of Medicinal Plants Using DNA Barcoding Technique

Pang¹,

Chen²

2019

Encyclopedia of Analytical Chemistry

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Medicinal plants have been used in the health care system in China for thousands of years. The correct identification of these plants is a prerequisite for their safe application. At present, the traditional methods are insufficient to meet the demands of identification, and a rapid and accurate method for authentication of medicinal plants is needed. DNA barcoding, a technique aiming at detecting species‐specific differences in a short region of DNA, provides a new powerful tool toward addressing this problem. Recently, ITS2 (second internal transcribed spacer) barcode has been broadly recognized and widely applied in the discrimination of herbs, and a publically available DNA barcoding system for identifying herbs has been established. Principles for identification of herbs using DNA barcoding have been embodied into the Chinese Pharmacopoeia. In this article, we introduce the DNA barcoding technique and determine its usage in discriminating medicinal plants, as well as its advantages and limitations.

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BLOG 2.0: a software system for character‐based species classification with DNA Barcode sequences. What it does, how to use it

Cited by 75 publications

References 14 publications

Supervised DNA Barcodes species classification: analysis, comparisons and results

Supervised DNA Barcodes species classification: analysis, comparisons and results

Applying DNA barcoding to conservation practice: a case study of endangered birds and large mammals in China

Identification of Medicinal Plants Using DNA Barcoding Technique

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