Similarity-based Identification Research Articles

To Extend or Not to Extend? Enriching a Corpus with Complementary and Related Documents

An agent in pursuit of a task may work with a corpus of documents with linked subjective content descriptions. Performing the task of document retrieval for a user or aiming to extend its own corpus, an agent so far relies on similarity measures to identify related documents. However, similarity may not be appropriate if looking for new information or different aspects of the same content. Therefore, this paper combines complementarity- and similarity-based identification of documents, specifically, contributing (i) a formal definition of complementarity using the available subjective content descriptions in the form of relational tuples as well as a taxonomy interrelating the concepts of the tuples, (ii) a technique for classifying complementary and related documents in one go, and (iii) a case study assessing the classification performance for complementary and related documents.

Complete vertebrate mitogenomes reveal widespread repeats and gene duplications

BackgroundModern sequencing technologies should make the assembly of the relatively small mitochondrial genomes an easy undertaking. However, few tools exist that address mitochondrial assembly directly.ResultsAs part of the Vertebrate Genomes Project (VGP) we develop mitoVGP, a fully automated pipeline for similarity-based identification of mitochondrial reads and de novo assembly of mitochondrial genomes that incorporates both long (> 10 kbp, PacBio or Nanopore) and short (100–300 bp, Illumina) reads. Our pipeline leads to successful complete mitogenome assemblies of 100 vertebrate species of the VGP. We observe that tissue type and library size selection have considerable impact on mitogenome sequencing and assembly. Comparing our assemblies to purportedly complete reference mitogenomes based on short-read sequencing, we identify errors, missing sequences, and incomplete genes in those references, particularly in repetitive regions. Our assemblies also identify novel gene region duplications. The presence of repeats and duplications in over half of the species herein assembled indicates that their occurrence is a principle of mitochondrial structure rather than an exception, shedding new light on mitochondrial genome evolution and organization.ConclusionsOur results indicate that even in the “simple” case of vertebrate mitogenomes the completeness of many currently available reference sequences can be further improved, and caution should be exercised before claiming the complete assembly of a mitogenome, particularly from short reads alone.

DNA barcoding of Momordica species and assessment of adulteration in Momordica herbal products, an anti-diabetic drug

Medicinal plants and their products have been used virtually in all cultures as a source of medicine since time immemorial. In India, several plant species are used as a medicine and in recent years, the trade-in medicinal plants have increased several folds. However, with burgeoning demand for raw herbal products, there has been concern over the safety and efficacy of raw herbal material as well as herbal products that contain only the desired plant species or labeled plant's product. In the present investigation, an emphasis was made to evaluate the extent of species adulteration in the raw herbal trade of Momordica charantia which is commonly called “karela” and used as alternate herbal medicine in the treatment of type-2 diabetes in south India. DNA barcodes were developed for six authentic reference species of Momordica and for the eighteen samples purchased from major raw herbal material distributors of south India representing the raw herbal products of M. charantia sold as “karela” in India. The DNA barcodes were developed using the nuclear region of the internal transcribed spacer (ITS) and the chloroplast region matK of six Momordica species, the biological reference standard, and the raw herbal drug trade samples. The species-level authenticity of the herbal drug samples was assessed adopting two identification methods namely BLAST similarity-based identification and phylogenetic tree approach. Our results indicate that the market samples sold were mostly authentic M. charantia except three. The present study offers a novel and reliable DNA barcode sequence-based approach for screening the species authenticity of raw herbal drug market samples of M. charantia and we have discussed the implications of the study in the larger context of authentication in raw herbal trade.

GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.

Unidentifiable by morphology: DNA barcoding of plant material in local markets in Iran.

Local markets provide a rapid insight into the medicinal plants growing in a region as well as local traditional health concerns. Identification of market plant material can be challenging as plants are often sold in dried or processed forms. In this study, three approaches of DNA barcoding-based molecular identification of market samples are evaluated, two objective sequence matching approaches and an integrative approach that coalesces sequence matching with a priori and a posteriori data from other markers, morphology, ethnoclassification and species distribution. Plant samples from markets and herbal shops were identified using morphology, descriptions of local use, and vernacular names with relevant floras and pharmacopoeias. DNA barcoding was used for identification of samples that could not be identified to species level using morphology. Two methods based on BLAST similarity-based identification, were compared with an integrative identification approach. Integrative identification combining the optimized similarity-based approach with a priori and a posteriori information resulted in a 1.67, 1.95 and 2.00 fold increase for ITS, trnL-F spacer, and both combined, respectively. DNA barcoding of traded plant material requires objective strategies to include data from multiple markers, morphology, and traditional knowledge to optimize species level identification success.

Identifying gastropod spawn from DNA barcodes: possible but not yet practicable

Identifying life stages of species with complex life histories is problematic as species are often only known and/or described from a single stage. DNA barcoding has been touted as an important tool for linking life-history stages of the same species. To test the current efficacy of DNA barcodes for identifying unknown mollusk life stages, 24 marine gastropod egg capsules were collected off the Philippines in deep water and sequenced for partial fragments of the COI, 16S and 12S mitochondrial genes. Two egg capsules of known shallow-water Mediterranean species were used to calibrate the method. These sequences were compared to those available in GenBank and the Barcode of Life Database (BOLD). Using COI sequences alone, only a single Mediterranean egg capsule was identified to species, and a single Philippine egg capsule was identified tentatively to genus; all other COI sequences recovered matches between 76% and 90% with sequences from BOLD and GenBank. Similarity-based identification using all three markers confirmed the Mediterranean specimens' identifications. A phylogenetic approach was also implemented to confirm similarity-based identifications and provide a higher-taxonomic identification when species-level identifications were not possible. Comparison of available GenBank sequences to the diversity curve of a well-sampled coral reef habitat in New Caledonia highlights the poor taxonomic coverage achieved at present in existing genetic databases, emphasizing the need to develop DNA barcoding projects for megadiverse and often taxonomically challenging groups such as mollusks, to fully realize its potential as an identification and discovery tool.

CHASE, a charge-assisted sequencing algorithm for automated homology-based protein identifications with matrix-assisted laser desorption/ionization time-of-flight post-source decay fragmentation data

We describe CHASE, a novel algorithm for automated de novo sequencing based on the mass spectrometric (MS) fragmentation analysis of tryptic peptides. This algorithm is used for protein identification from sequence similarity criteria and consists of four steps: (1) derivatization of tryptic peptides at the N-terminus with a negatively charged reagent; (2) post-source decay (PSD) fragmentation analysis of peptides; (3) interpretation of the mass peaks with the CHASE algorithm and reconstruction of the amino acid sequence; (4) transfer of these data to software for protein identifications based on sequence homology (Basic Local Alignment Search Tool, BLAST). This procedure deduced the correct amino acid sequence of tryptic peptide samples and also was able to deduce the correct sequence from difficult mass patterns and identify the amino acid sequence. This allows complete automation of the process starting from MS fragmentation of complex peptide mixtures at low concentration (e.g. from silver-stained gel bands) to identification of the protein. We also show that if PSD data are collected in a single spectrum (instead of the segmented mode offered by conventional matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) instrumentation), the complete workflow from MS-PSD data acquisition to similarity-based identification can be completely automated. This strategy may be applied to proteomic studies for protein identification based on automated de novo sequencing instead of MS or tandem MS patterns. We describe the Charge Assisted Sequencing Engine (CHASE) algorithm, the working protocol, the performance of the algorithm on spectra from MALDI-TOFMS and the data comparison between a TOF and a TOF-TOF instrument.

GalaxieEST: addressing EST identity through automated phylogenetic analysis

BackgroundResearch involving expressed sequence tags (ESTs) is intricately coupled to the existence of large, well-annotated sequence repositories. Comparatively complete and satisfactory annotated public sequence libraries are, however, available only for a limited range of organisms, rendering the absence of sequences and gene structure information a tangible problem for those working with taxa lacking an EST or genome sequencing project. Paralogous genes belonging to the same gene family but distinguished by derived characteristics are particularly prone to misidentification and erroneous annotation; high but incomplete levels of sequence similarity are typically difficult to interpret and have formed the basis of many unsubstantiated assumptions of orthology.In these cases, a phylogenetic study of the query sequence together with the most similar sequences in the database may be of great value to the identification process. In order to facilitate this laborious procedure, a project to employ automated phylogenetic analysis in the identification of ESTs was initiated.ResultsgalaxieEST is an open source Perl-CGI script package designed to complement traditional similarity-based identification of EST sequences through employment of automated phylogenetic analysis. It uses a series of BLAST runs as a sieve to retrieve nucleotide and protein sequences for inclusion in neighbour joining and parsimony analyses; the output includes the BLAST output, the results of the phylogenetic analyses, and the corresponding multiple alignments. galaxieEST is available as an on-line web service for identification of fungal ESTs and for download / local installation for use with any organism group at .ConclusionsBy addressing sequence relatedness in addition to similarity, galaxieEST provides an integrative view on EST origin and identity, which may prove particularly useful in cases where similarity searches return one or more pertinent, but not full, matches and additional information on the query EST is needed.

An ontology for pharmaceutical ligands and its application for in silico screening and library design.

Annotation efforts in biosciences have focused in past years mainly on the annotation of genomic sequences. Only very limited effort has been put into annotation schemes for pharmaceutical ligands. Here we propose annotation schemes for the ligands of four major target classes, enzymes, G protein-coupled receptors (GPCRs), nuclear receptors (NRs), and ligand-gated ion channels (LGICs), and outline their usage for in silico screening and combinatorial library design. The proposed schemes cover ligand functionality and hierarchical levels of target classification. The classification schemes are based on those established by the EC, GPCRDB, NuclearDB, and LGICDB. The ligands of the MDL Drug Data Report (MDDR) database serve as a reference data set of known pharmacologically active compounds. All ligands were annotated according to the schemes when attribution was possible based on the activity classification provided by the reference database. The purpose of the ligand-target classification schemes is to allow annotation-based searching of the ligand database. In addition, the biological sequence information of the target is directly linkable to the ligand, hereby allowing sequence similarity-based identification of ligands of next homologous receptors. Ligands of specified levels can easily be retrieved to serve as comprehensive reference sets for cheminformatics-based similarity searches and for design of target class focused compound libraries. Retrospective in silico screening experiments within the MDDR01.1 database, searching for structures binding to dopamine D2, all dopamine receptors and all amine-binding class A GPCRs using known dopamine D2 binding compounds as a reference set, have shown that such reference sets are in particular useful for the identification of ligands binding to receptors closely related to the reference system. The potential for ligand identification drops with increasing phylogenetic distance. The analysis of the focus of a tertiary amine based combinatorial library compared to known amine binding class A GPCRs, peptide binding class A GPCRs, and LGIC ligands constitutes a second application scenario which illustrates how the focus of a combinatorial library can be treated quantitatively. The provided annotation schemes, which bridge chem- and bioinformatics by linking ligands to sequences, are expected to be of key utility for further systematic chemogenomics exploration of previously well explored target families.