Both and Neither: in silico v1.0, Ecce Homology

Leonardo ◽  
2005 ◽  
Vol 38 (4) ◽  
pp. 286-293 ◽  
Author(s):  
Ruth West ◽  
Jeff Burke ◽  
Cheryl Kerfeld ◽  
Eitan Mendelowitz ◽  
Thomas Holton ◽  
...  
Keyword(s):  
Computer Vision ◽  
User Interface ◽  
Comparative Genomics ◽  
New Media ◽  
In Silico ◽  
Genetic Data ◽  
Installation Space ◽  
Local Alignment ◽  
Search Tool ◽  
Media Work

Ecce Homology, a physically interactive new-media work, visualizes genetic data as calligraphic forms. A novel computer-vision user interface allows multiple participants, through their movement in the installation space, to select genes from the human genome for visualizing the Basic Local Alignment Search Tool (BLAST), a primary algorithm in comparative genomics. Ecce Homology was successfully installed in the UCLA Fowler Museum, 6 November 2003–4 January 2004.

Leveraging the power of new molecular technologies in the clinical setting requires unprecedented awareness of limitations and drawbacks: experience of one diagnostic laboratory

2018 ◽  
Vol 56 (6) ◽  
pp. 408-412 ◽  
Author(s):  
Landry Nfonsam ◽  
Shelley Ordorica ◽  
Mahdi Ghani ◽  
Ryan Potter ◽  
Audrey Schaffer ◽  
...  
Keyword(s):  
In Silico ◽  
Variant Calling ◽  
Connective Tissue Disorder ◽  
Local Alignment ◽  
Segmental Duplications ◽  
Diagnostic Laboratory ◽  
Prediction Tools ◽  
Search Tool ◽  
In Silico Models ◽  
The University

BackgroundAdvances in molecular technologies and in-silico variant prediction tools offer wide-ranging opportunities in diagnostic settings, yet they also present with significant limitations.ObjectiveHere, we contextualise the limitations of next-generation sequencing (NGS), multiplex ligation-dependent probe amplification (MLPA) and in-silico prediction tools routinely used by diagnostic laboratories by reviewing specific experiences from our diagnostic laboratory.MethodsWe investigated discordant annotations and/or incorrect variant ‘callings’ in exons of 56 genes constituting our cardiomyopathy and connective tissue disorder NGS panels. Discordant variants and segmental duplications (SD) were queried using the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool and the University of California Santa Cruz genome browser, respectively, to identify regions of high homology. Discrepant variant analyses by in-silico models were re-evaluated using updated file entries.ResultsWe observed a 5% error rate in MYH7 variant ‘calling’ using MLPA, which resulted from >90% homology of the MYH7 probe-binding site to MYH6. SDs were detected in TTN, PKP2 and MYLK. SDs in MYLK presented the highest risk (15.7%) of incorrect variant ‘calling’. The inaccurate ‘callings’ and discrepant in-silico predictions were resolved following detailed investigation into the source of error.ConclusionRecognising the limitations described here may help avoid incorrect diagnoses and leverage the power of new molecular technologies in diagnostic settings.

scholarly journals Not just BLAST nt: WGS database joins the party

2019 ◽  
Author(s):  
Jose Manuel Martí ◽  
Carlos P. Garay
Keyword(s):  
Molecular Biology ◽  
Computational Biology ◽  
In Silico ◽  
Confidence Score ◽  
Taxonomic Classification ◽  
Local Alignment ◽  
Whole Genome ◽  
Culture Independent ◽  
Search Tool ◽  
Ncbi Blast

AbstractSince its introduction in 1990 and with over 50k citations, the NCBI BLAST family has been an essential tool of in silico molecular biology. The BLAST nt database, based on the traditional divisions of GenBank, has been the default and most comprehensive database for nucleotide BLAST searches and for taxonomic classification software in metagenomics. Here we argue that this is no longer the case. Currently, the NCBI WGS database contains one billion reads (almost five times more than GenBank), and with 4.4 trillion nucleotides, WGS has about 14 times more nucleotides than GenBank. This ratio is growing with time. We advocate a change in the database paradigm in taxonomic classification by systematically combining the nt and WGS databases in order to boost taxonomic classifiers sensitivity. We present here a case in which, by adding WGS data, we obtained over five times more classified reads and with a higher confidence score. To facilitate the adoption of this approach, we provide the draftGenomes script.Author summaryCulture-independent methods are revolutionizing biology. The NIH/NCBI Basic Local Alignment Search Tool (BLAST) is one of the most widely used methods in computational biology. The BLAST nt database has become a de facto standard for taxonomic classifiers in metagenomics. We believe that it is time for a change in the database paradigm for such a classification. We advocate the systematic combination of the BLAST nt database with genomes of the massive NCBI Whole-Genome Shotgun (WGS) database. We make draftGenomes available, a script that eases the adoption of this approach. Current developments and technologies make it feasible now. Our recent results in several metagenomic projects indicate that this strategy boosts the sensitivity in taxonomic classifications.

scholarly journals In silico analysis of V48A dihydropteroate synthase mutation to dapsone on Mycobacterium leprae from Papua

2020 ◽  
Vol 11 (2) ◽  
pp. 70-76
Author(s):  
Yustinus Maladan ◽  
Hana Krismawati ◽  
Hotma Martogi Laurensia Hutapea ◽  
Antonius Oktavian
Keyword(s):  
Molecular Docking ◽  
In Silico ◽  
Mycobacterium Leprae ◽  
Gene Bank ◽  
Local Alignment ◽  
Autodock Vina ◽  
Docking Analysis ◽  
Dihydropteroate Synthase ◽  
Search Tool

Latar belakang: Lepra merupakan penyakit yang disebabkan oleh Mycobacterium leprae. Resistensi obat merupakan salah satu tantangan dalam pemberantasan kusta khususnya di Papua. Adanya mutasi pada gen folP1 penyandi dihydropteroate synthase (DHPS) merupakan dasar untuk deteksi molekuler resistensi dapson pada penyakit lepra. Tujuan penelitian ini adalah mendeteksi mutasi pada gen folP1 Mycobacterium leprae dari Papua, Indonesia dan menganalisis pengaruh mutasi tersebut terhadap dapson dengan metode in silico. Metode: Identifikasi mutasi pada gen folp1 M. leprae dilakukan melalui proses Basic Local Alignment Search Tool (BLAST) di gene bank. Analisis efek mutasi dengan menggunakan server Have (y) Our Protein Explained (HOPE). Prediksi binding pocket menggunakan Computed Atlas of Surface Topography of proteins (CASTp). Homologi modeling struktur 3D DHPS menggunakan server Iterative Threading ASSEmbly Refinement (I TASSER). Analisis docking dengan menggunakan AutoDock Vina yang terintegrasi dengan aplikasi Python Prescription (PyRx). Hasil: Hasil sekuensing menunjukkan adanya variasi dalam gen folP1 M. leprae yaitu perubahan dari Timin (T) menjadi Sitosin (C) pada nukleotida 143. Residu yang bermutasi (V48A) terletak pada domain yang penting untuk aktivitas protein dan kontak dengan residu di domain lain. Ada kemungkinan bahwa interaksi ini penting untuk fungsi protein secara benar. Mutan V48A tidak banyak mempengaruhi stabilitas dari dihydropteroate synthase M. leprae. Kesimpulan: Berdasarkan analisis molecular docking, mutasi V48A tidak mempengaruhi binding affinity dapson terhadap dihydropteroate synthase M. leprae. Hasil ini menunjukkan mutan V48A kemungkinan tetaprentan terhadap dapson. Dengan demikian perlu dilakukan uji in vivo untuk mengkofirmasi efek mutasi V48A. Kata kunci: Mycobacterium leprae, folP1 gene, dihydropteroate synthase, dapson   Abstract Background: Leprosy is a disease caused by Mycobacterium leprae. Drug resistance is one of the challenges in leprosy elimination especially in Papua. The presence of mutations in folP1 gene that encode dihydropteroate synthase (DHPS) was considered as the exclusive basis for molecular detection of dapsone resistance in leprosy. The objective of this study was to detect mutations in the folP1 gene of Mycobacterium leprae from Papua, Indonesia and to analyze the effect of these mutations on dapsone using the in-silico method. Methods: Identification of mutations in the folp1 M. leprae gene is carried out through the Basic Local Alignment Search Tool (BLAST) process in the gene bank. The analysis of the effects of mutations using the Have (y)Our Protein Explained (HOPE) server. Bindings pocket prediction is done using the Computed Atlas of Surface Topography of proteins (CASTp). Homology modeling 3D structure of DHPS using the Iterative Threading ASSEmbly Refinement (I-TASSER) server. Docking analysis was performed using AutoDock Vina which is integrated with the Python Prescription (PyRx) application. Results: The sequencing results showed a variation in the folP1 M. leprae gene, namely a change from thymine (T) to cytosine (C) in nucleotide 143. The mutated residue (V48A) is in a domain that is essential for the activity of the protein and in contact with residues in another domain. It is possible that this interaction is important for the correct function of the protein. V48A mutants did not significantly affect the stability of DHPS M. leprae. Conclusion: Based on molecular docking analysis, this mutation does not affect binding affinity dapsone against M. leprae dihydropteroate synthase. These results indicate that the V48A mutant is likely to remain susceptible to dapsone. Thus, it is necessary to do an in vivo test to confirm the effect of the V48A mutation. Keywords: Mycobacterium leprae, folP1 gene, dihydropteroate synthase, dapsone

Analysis of New Media Work Call of Childlike Innocence

2020 ◽  
Vol 7 (4) ◽  
pp. 30-34
Author(s):  
Yin Lu ◽  
Surng Gahb Jahng
Keyword(s):  
New Media ◽  
Media Work

The Influence of Memory-Aware Computation on Distributed BLAST

2019 ◽  
Vol 14 (2) ◽  
pp. 157-163
Author(s):  
Majid Hajibaba ◽  
Mohsen Sharifi ◽  
Saeid Gorgin
Keyword(s):  
Search Time ◽  
Genomic Research ◽  
Local Alignment ◽  
Negative Effects ◽  
Sequencing Technologies ◽  
Percent Improvement ◽  
Fast Processing ◽  
Search Tool ◽  
Memory Awareness ◽  
Generation Sequencing

Background: One of the pivotal challenges in nowadays genomic research domain is the fast processing of voluminous data such as the ones engendered by high-throughput Next-Generation Sequencing technologies. On the other hand, BLAST (Basic Local Alignment Search Tool), a longestablished and renowned tool in Bioinformatics, has shown to be incredibly slow in this regard. Objective: To improve the performance of BLAST in the processing of voluminous data, we have applied a novel memory-aware technique to BLAST for faster parallel processing of voluminous data. Method: We have used a master-worker model for the processing of voluminous data alongside a memory-aware technique in which the master partitions the whole data in equal chunks, one chunk for each worker, and consequently each worker further splits and formats its allocated data chunk according to the size of its memory. Each worker searches every split data one-by-one through a list of queries. Results: We have chosen a list of queries with different lengths to run insensitive searches in a huge database called UniProtKB/TrEMBL. Our experiments show 20 percent improvement in performance when workers used our proposed memory-aware technique compared to when they were not memory aware. Comparatively, experiments show even higher performance improvement, approximately 50 percent, when we applied our memory-aware technique to mpiBLAST. Conclusion: We have shown that memory-awareness in formatting bulky database, when running BLAST, can improve performance significantly, while preventing unexpected crashes in low-memory environments. Even though distributed computing attempts to mitigate search time by partitioning and distributing database portions, our memory-aware technique alleviates negative effects of page-faults on performance.

The Power of Matrix Factorization: Methods for Deconvoluting Genetic Heterogeneous Data at Expression Level

2021 ◽  
Vol 15 (8) ◽  
pp. 841-853
Author(s):  
Yuan Liu ◽  
Zhining Wen ◽  
Menglong Li
Keyword(s):  
Artificial Intelligence ◽  
Matrix Factorization ◽  
In Silico ◽  
Genetic Data ◽  
Heterogeneous Data ◽  
Expression Level ◽  
Mathematical Methods ◽  
Challenges And Opportunities ◽  
Factorization Methods ◽  
Genetic Profiles

Background:: The utilization of genetic data to investigate biological problems has recently become a vital approach. However, it is undeniable that the heterogeneity of original samples at the biological level is usually ignored when utilizing genetic data. Different cell-constitutions of a sample could differentiate the expression profile, and set considerable biases for downstream research. Matrix factorization (MF) which originated as a set of mathematical methods, has contributed massively to deconvoluting genetic profiles in silico, especially at the expression level. Objective: With the development of artificial intelligence algorithms and machine learning, the number of computational methods for solving heterogeneous problems is also rapidly abundant. However, a structural view from the angle of using MF to deconvolute genetic data is quite limited. This study was conducted to review the usages of MF methods on heterogeneous problems of genetic data on expression level. Methods: MF methods involved in deconvolution were reviewed according to their individual strengths. The demonstration is presented separately into three sections: application scenarios, method categories and summarization for tools. Specifically, application scenarios defined deconvoluting problem with applying scenarios. Method categories summarized MF algorithms contributed to different scenarios. Summarization for tools listed functions and developed web-servers over the latest decade. Additionally, challenges and opportunities of relative fields are discussed. Results and Conclusion: Based on the investigation, this study aims to present a relatively global picture to assist researchers to achieve a quicker access of deconvoluting genetic data in silico, further to help researchers in selecting suitable MF methods based on the different scenarios.

scholarly journals Predicting bacteriophage hosts based on sequences of annotated receptor-binding proteins

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dimitri Boeckaerts ◽  
Michiel Stock ◽  
Bjorn Criel ◽  
Hans Gerstmans ◽  
Bernard De Baets ◽  
...  
Keyword(s):  
Machine Learning ◽  
Predictive Model ◽  
Receptor Binding ◽  
Bacterial Infections ◽  
Sequence Data ◽  
Sequence Similarity ◽  
Area Under The Curve ◽  
Local Alignment ◽  
Search Tool ◽  
Different Levels

AbstractNowadays, bacteriophages are increasingly considered as an alternative treatment for a variety of bacterial infections in cases where classical antibiotics have become ineffective. However, characterizing the host specificity of phages remains a labor- and time-intensive process. In order to alleviate this burden, we have developed a new machine-learning-based pipeline to predict bacteriophage hosts based on annotated receptor-binding protein (RBP) sequence data. We focus on predicting bacterial hosts from the ESKAPE group, Escherichia coli, Salmonella enterica and Clostridium difficile. We compare the performance of our predictive model with that of the widely used Basic Local Alignment Search Tool (BLAST). Our best-performing predictive model reaches Precision-Recall Area Under the Curve (PR-AUC) scores between 73.6 and 93.8% for different levels of sequence similarity in the collected data. Our model reaches a performance comparable to that of BLASTp when sequence similarity in the data is high and starts outperforming BLASTp when sequence similarity drops below 75%. Therefore, our machine learning methods can be especially useful in settings in which sequence similarity to other known sequences is low. Predicting the hosts of novel metagenomic RBP sequences could extend our toolbox to tune the host spectrum of phages or phage tail-like bacteriocins by swapping RBPs.

scholarly journals Kelch 13-propeller polymorphisms in Plasmodium falciparum from Jazan region, southwest Saudi Arabia

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Ommer Mohammed Dafalla ◽  
Mohammed Alzahrani ◽  
Ahmed Sahli ◽  
Mohammed Abdulla Al Helal ◽  
Mohammad Mohammad Alhazmi ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Saudi Arabia ◽  
Parasite Clearance ◽  
Sub Saharan Africa ◽  
Local Alignment ◽  
Nucleotide Polymorphisms ◽  
Gene Encoding ◽  
Synonymous Mutations ◽  
Search Tool ◽  
Sub Saharan

Abstract Background Artemisinin-based combination therapy (ACT) is recommended at the initial phase for treatment of Plasmodium falciparum, to reduce morbidity and mortality in all countries where malaria is endemic. Polymorphism in portions of P. falciparum gene encoding kelch (K13)-propeller domains is associated with delayed parasite clearance after ACT. Of about 124 different non-synonymous mutations, 46 have been identified in Southeast Asia (SEA), 62 in sub-Saharan Africa (SSA) and 16 in both the regions. This is the first study designed to analyse the prevalence of polymorphism in the P. falciparum k13-propeller domain in the Jazan region of southwest Saudi Arabia, where malaria is endemic. Methods One-hundred and forty P. falciparum samples were collected from Jazan region of southwest Saudi Arabia at three different times: 20 samples in 2011, 40 samples in 2016 and 80 samples in 2020 after the implementation of ACT. Plasmodium falciparum kelch13 (k13) gene DNA was extracted, amplified, sequenced, and analysed using a basic local alignment search tool (BLAST). Results This study obtained 51 non-synonymous (NS) mutations in three time groups, divided as follows: 6 single nucleotide polymorphisms (SNPs) ‘11.8%’ in samples collected in 2011 only, 3 (5.9%) in 2011and 2016, 5 (9.8%) in 2011 and 2020, 5 (9.8%) in 2016 only, 8 (15.7%) in 2016 and 2020, 14 (27.5%) in 2020 and 10 (19.6%) in all the groups. The BLAST revealed that the 2011 isolates were genetically closer to African isolates (53.3%) than Asian ones (46.7%). Interestingly, this proportion changed completely in 2020, to become closer to Asian isolates (81.6%) than to African ones (18.4%). Conclusions Despite the diversity of the identified mutations in the k13-propeller gene, these data did not report widespread artemisinin-resistant polymorphisms in the Jazan region where these samples were collected. Such a process would be expected to increase frequencies of mutations associated with the resistance of ACT.

Identification of Salmonella enterica Serovar Typhimurium Using Specific PCR Primers Obtained by Comparative Genomics in Salmonella Serovars

2006 ◽  
Vol 69 (7) ◽  
pp. 1653-1661 ◽  
Author(s):  
H. J. KIM ◽  
S. H. PARK ◽  
T. H. LEE ◽  
B. H. NAHM ◽  
Y. H. CHUNG ◽  
...  
Keyword(s):  
Comparative Genomics ◽  
Salmonella Enterica ◽  
Target Genes ◽  
Salmonella Enterica Serovar Typhimurium ◽  
Foodborne Pathogen ◽  
Pcr Primers ◽  
Genomic Sequences ◽  
Local Alignment ◽  
Serovar Typhimurium ◽  
Salmonella Serovars

Salmonella enterica serovar Typhimurium is a major foodborne pathogen throughout the world. Until now, the specific target genes for the detection and identification of serovar Typhimurium have not been developed. To determine the specific probes for serovar Typhimurium, the genes of serovar Typhimurium LT2 that were expected to be unique were selected with the BLAST (Basic Local Alignment Search Tool) program within GenBank. The selected genes were compared with 11 genomic sequences of various Salmonella serovars by BLAST. Of these selected genes, 10 were expected to be specific to serovar Typhimurium and were not related to virulence factor genes of Salmonella pathogenicity island or to genes of the O and H antigens of Salmonella. Primers for the 10 selected genes were constructed, and PCRs were evaluated with various genomic DNAs of Salmonella and non-Salmonella strains for the specific identification of Salmonella serovar Typhimurium. Among all the primer sets for the 10 genes, STM4497 showed the highest degree of specificity to serovar Typhimurium. In this study, a specific primer set for Salmonella serovar Typhimurium was developed on the basis of the comparison of genomic sequences between Salmonella serovars and was validated with PCR. This method of comparative genomics to select target genes or sequences can be applied to the specific detection of microorganisms.

scholarly journals Media skills for daily life: Designing a journalism programme for graduates of all disciplines

2011 ◽  
Vol 17 (1) ◽  
pp. 141-156
Author(s):  
Lee Duffield
Keyword(s):  
New Media ◽  
Community Of Practice ◽  
Academic Discipline ◽  
Journalism Education ◽  
Preliminary Conclusion ◽  
Media Audiences ◽  
The Subject ◽  
The Common ◽  
Media Work ◽  
Journalism Students

This article in the journalism education field reports on the construction of a new subject as part of a postgraduate coursework degree. The subject, or unit will offer both Journalism students and other students an introductory experience of creating media, using common ‘new media’ tools, with exercises that will model the learning of communication principles through practice. It has been named ‘Fundamental Media Skills for the Workplace’. The conceptualisation and teaching of it will be characteristic of the Journalism academic discipline that uses the ‘inside perspective’—understanding mass media by observing from within. Proposers for the unit within the Journalism discipline have sought to extend the common teaching approach, based on training to produce start-ready recruits for media jobs, backed by a study of contexts, e.g. journalistic ethics, or media audiences. In this proposal, students would then examine the process to elicit additional knowledge about their learning. The article draws on literature of journalism and its pedagogy, and on communication generally. It also documents a ‘community of practice’ exercise conducted among practitioners as teachers for the subject, developing exercises and models of media work. A preliminary conclusion from that exercise is that it has taken a step towards enhancing skills-based learning for media work.

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