scholarly journals Analyzing Genomic Data Using Tensor-Based Orthogonal Polynomials with Application to Synthetic RNAs

2020 ◽  
Author(s):  
Saba Nafees ◽  
Sean H. Rice ◽  
Catherine A. Wakeman

ABSTRACTAn important goal in molecular biology is to quantify both the patterns across a genomic sequence and the relationship between phenotype and underlying sequence. We propose a multivariate tensor-based orthogonal polynomial approach to characterize nucleotides or amino acids in a given sequence and map corresponding phenotypes onto the sequence space. We have applied this method to a previously published case of small transcription activating RNAs (STARs). Covariance patterns along the sequence showcased strong correlations between nucleotides at the ends of the sequence. However, when the phenotype is projected onto the sequence space, this pattern doesn’t emerge. When doing second order analysis and quantifying the functional relationship between the phenotype and pairs of sites along the sequence, we identified sites with high regressions spread across the sequence, indicating potential intramolecular binding. In addition to quantifying interactions between different parts of a sequence, the method quantifies sequence-phenotype interactions at first and higher order levels. We discuss the strengths and constraints of the method and compare it to computational methods such as machine learning approaches. An accompanying command line tool to compute these polynomials is provided. We show proof of concept of this approach and demonstrate its potential application to other biological systems.

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Saba Nafees ◽  
Sean H Rice ◽  
Catherine A Wakeman

Abstract An important goal in molecular biology is to quantify both the patterns across a genomic sequence and the relationship between phenotype and underlying sequence. We propose a multivariate tensor-based orthogonal polynomial approach to characterize nucleotides or amino acids in a given sequence and map corresponding phenotypes onto the sequence space. We have applied this method to a previously published case of small transcription activating RNAs. Covariance patterns along the sequence showcased strong correlations between nucleotides at the ends of the sequence. However, when the phenotype is projected onto the sequence space, this pattern does not emerge. When doing second order analysis and quantifying the functional relationship between the phenotype and pairs of sites along the sequence, we identified sites with high regressions spread across the sequence, indicating potential intramolecular binding. In addition to quantifying interactions between different parts of a sequence, the method quantifies sequence–phenotype interactions at first and higher order levels. We discuss the strengths and constraints of the method and compare it to computational methods such as machine learning approaches. An accompanying command line tool to compute these polynomials is provided. We show proof of concept of this approach and demonstrate its potential application to other biological systems.


2019 ◽  
Author(s):  
Yajnavalka Banerjee ◽  
Aya Akhras ◽  
Amar Hassan Khamis ◽  
Alawi Alsheikh-Ali ◽  
David Davis

BACKGROUND The evolution of an undergraduate medical student into an adept physician is perpetual, demanding, and stressful. Several studies have indicated medical students have a higher predominance of mental health problems than other student groups of the same age, where medical education acts as a stressor and may lead to unfavorable consequences such as depression, burnout, somatic complaints, decrease in empathy, dismal thoughts about quitting medical school, self harm and suicidal ideation, and poor academic performance. It is imperative to determine the association between important psychoeducational variables and academic performance in the context of medical education to comprehend the response to academic stress. OBJECTIVE The aim of this proof-of-concept study is to determine the relationship between resilience, learning approaches, and stress-coping strategies and how they can collectively predict achievement in undergraduate medical students. The following research questions will be addressed: What is the correlation between the psychoeducational variables resilience, learning approaches, and stress-coping strategies? Can academic performance of undergraduate medical students be predicted through the construction of linear relationships between defined variables employing the principles of empirical modeling? METHODS Study population will consist of 234 students registered for the MBBS (Bachelor of Medicine, Bachelor of Surgery) at Mohammed Bin Rashid University of Medicine and Health Sciences distributed over 4 cohorts. Newly registered MBBS students will be excluded from the study. Various psychoeducational variables will be assessed using prevalidated questionnaires. For learning approaches assessment, the Approaches and Study Skills Inventory for Students questionnaire will be employed. Resilience and stress-coping strategies will be evaluated using the Wagnild-Young resilience scale and a coping strategies scale derived from Holahan and Moos’s Coping Strategies Scale, respectively. Independent variables (resilience, stress-coping strategies, and learning approaches) will be calculated. Scores will be tested for normality by using the Shapiro-Wilk test. An interitem correlational matrix of the dependent and independent variables to test pairwise correlation will be formed using Pearson bivariate correlation coefficients. Regression models will be used to answer our questions with type II analyses of variance in tests involving multiple predictors. Regression analyses will be checked for homogeneity of variance (Levine test) and normality of residuals and multicollinearity (variance inflation factor). Statistical significance will be set at 5% (alpha=.05). Effect sizes will be estimated with 95% CIs. RESULTS Psychoeducational instruments in the form of validated questionnaire have been identified in relation to the objectives. These questionnaires have been formatted for integration into Google forms such that they can be electronically distributed to the consenting participants. We submitted the proposal to MBRU institutional review board (IRB) for which exemption has been awarded (application ID: MBRU-IRB-2019-013). There is no funding in place for this study and no anticipated start date. Total duration of the proposed research is 12 months. CONCLUSIONS Psychoeducational instruments used in this study will correlate resilience, stress-coping strategies, and learning approaches to academic performance of undergradudate medical students. To the best of our knowledge, no study exploring the multidimensional association of key psychoeducational variables and academic performance in undergraduate medical students has been pursued. Investigated variables, resilience, learning approaches, and stress-coping strategies, are individual traits, however; students’ learning history before they joined MBRU is unknown, so our research will not be able to address this specific aspect. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) PRR1-10.2196/14677


10.2196/14677 ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. e14677 ◽  
Author(s):  
Yajnavalka Banerjee ◽  
Aya Akhras ◽  
Amar Hassan Khamis ◽  
Alawi Alsheikh-Ali ◽  
David Davis

Background The evolution of an undergraduate medical student into an adept physician is perpetual, demanding, and stressful. Several studies have indicated medical students have a higher predominance of mental health problems than other student groups of the same age, where medical education acts as a stressor and may lead to unfavorable consequences such as depression, burnout, somatic complaints, decrease in empathy, dismal thoughts about quitting medical school, self harm and suicidal ideation, and poor academic performance. It is imperative to determine the association between important psychoeducational variables and academic performance in the context of medical education to comprehend the response to academic stress. Objective The aim of this proof-of-concept study is to determine the relationship between resilience, learning approaches, and stress-coping strategies and how they can collectively predict achievement in undergraduate medical students. The following research questions will be addressed: What is the correlation between the psychoeducational variables resilience, learning approaches, and stress-coping strategies? Can academic performance of undergraduate medical students be predicted through the construction of linear relationships between defined variables employing the principles of empirical modeling? Methods Study population will consist of 234 students registered for the MBBS (Bachelor of Medicine, Bachelor of Surgery) at Mohammed Bin Rashid University of Medicine and Health Sciences distributed over 4 cohorts. Newly registered MBBS students will be excluded from the study. Various psychoeducational variables will be assessed using prevalidated questionnaires. For learning approaches assessment, the Approaches and Study Skills Inventory for Students questionnaire will be employed. Resilience and stress-coping strategies will be evaluated using the Wagnild-Young resilience scale and a coping strategies scale derived from Holahan and Moos’s Coping Strategies Scale, respectively. Independent variables (resilience, stress-coping strategies, and learning approaches) will be calculated. Scores will be tested for normality by using the Shapiro-Wilk test. An interitem correlational matrix of the dependent and independent variables to test pairwise correlation will be formed using Pearson bivariate correlation coefficients. Regression models will be used to answer our questions with type II analyses of variance in tests involving multiple predictors. Regression analyses will be checked for homogeneity of variance (Levine test) and normality of residuals and multicollinearity (variance inflation factor). Statistical significance will be set at 5% (alpha=.05). Effect sizes will be estimated with 95% CIs. Results Psychoeducational instruments in the form of validated questionnaire have been identified in relation to the objectives. These questionnaires have been formatted for integration into Google forms such that they can be electronically distributed to the consenting participants. We submitted the proposal to MBRU institutional review board (IRB) for which exemption has been awarded (application ID: MBRU-IRB-2019-013). There is no funding in place for this study and no anticipated start date. Total duration of the proposed research is 12 months. Conclusions Psychoeducational instruments used in this study will correlate resilience, stress-coping strategies, and learning approaches to academic performance of undergradudate medical students. To the best of our knowledge, no study exploring the multidimensional association of key psychoeducational variables and academic performance in undergraduate medical students has been pursued. Investigated variables, resilience, learning approaches, and stress-coping strategies, are individual traits, however; students’ learning history before they joined MBRU is unknown, so our research will not be able to address this specific aspect. International Registered Report Identifier (IRRID) PRR1-10.2196/14677


2011 ◽  
Vol 77 (10) ◽  
pp. 3532-3535 ◽  
Author(s):  
Caray A. Walker ◽  
Willie Donachie ◽  
David G. E. Smith ◽  
Michael C. Fontaine

ABSTRACTA two-step allele replacement mutagenesis procedure, using a conditionally replicating plasmid, was developed to allow the creation of targeted, marker-free mutations inCorynebacterium pseudotuberculosis. The relationship between homologous sequence length and recombination frequency was determined, and enhanced plasmid excision was observed due to the rolling-circle replication of the mutagenesis vector. Furthermore, an antibiotic enrichment procedure was applied to improve the recovery of mutants. Subsequently, as proof of concept, a marker-free,cp40-deficient mutant ofC. pseudotuberculosiswas constructed.


1979 ◽  
Vol 45 (1) ◽  
pp. 283-296
Author(s):  
Millicent E. Poole

This study investigated the relationship between linguistic code elaboration and verbal processing strategies. Individual, structured interviews were administered to a sample of 48 male and 48 female adolescents, aged between 15 and 16 yr., to obtain measures in two domains, linguistic and verbal. Interdomain relationships were explored by means of principal component analysis and canonical correlation. The pattern of relationships between the two domains suggested a functional relationship between the linguistic codes and task-specific verbal processing modes. That is to say, linguistic codes reflected the simplicity or complexity of verbal processing strategies needed for task completion.


2021 ◽  
Vol 6 (14) ◽  
pp. 89-97
Author(s):  
MUSTAFA ÖZYEŞİL ◽  
MOHAMMAD AL-TARIFI

Cryptocurrencies are a modern kind of financial instrument (Hudson & Urquhart, 2019), the first cryptocurrency is Bitcoin , proposed by who called Satoushi Nakamato (2008), as The open source was created on the proof-of-concept principle that transactions can be securely treated on a decentralized peer to peer network without the need for a central clearinghouse, which appeared 2009 ( Heid, 2013). The success of the bitcoin blazes a trail to what called ‘Altcoin” this expression means all the cryptocurrencies that set in motion after the victory of the bitcoin, these coins sell themselves as the best alternatives for the bitcoin (FRANKENFIELD, 2020) . There are many types for the altcoin. The third type of the cryptocurrency is called Tokens Unlike Bitcoin and Altcoins, tokens are not able to activate independently and are dependent on the grid of another cryptocurrency. That means they do not have their own core DLT or blockchain, but instead, are built on top of an existing cryptocurrency’s blockchain (Types of cryptocurrencies: explaining the major types of cryptos, 2019). The worth of bitcoin doesn’t depend on any tangible asset or economies of the countries while it is based upon the security of an algorithm which traces all transactions (Hudson & Urquhart, 2019). The studies determine the number of the bitcoin price development in the long -run (Ciaian, Rajcaniova, & Kancs, 2018): • Market forces of the Bitcoin supply and demand • The bitcoin’s attractiveness for the investors • The influence of global macro-financial developments If you're forming an investment strategy designed to help you trail long-term financial intentions, understanding the relationship between company size, return potential, and risk is vital. (Market cap—or market capitalization—refers to the total value of all a company's shares of stock, 2017) .Hence , Manifested importance a cryptocurrency’s market capitalization as the total values of all coins currently in circulation. the cryptocurrency’s market cap contains what’s called Bitcoin Dominance that is the ratio between the market cap of bitcoin to other coins of the cryptocurrency markets (jacobcanfield, 2019) . Cryptocurrency trade is attractive type of investment. this market treated the same of the foreign exchange and stock market ( Radityo, Munajat, & Budi, 2017). The investors using the same basic in investment (buy low, sell high) but they need to calculating the risks


BMC Genomics ◽  
2010 ◽  
Vol 11 (1) ◽  
pp. 271 ◽  
Author(s):  
Suzy C.P. Renn ◽  
Heather E. Machado ◽  
Albyn Jones ◽  
Kosha Soneji ◽  
Rob J. Kulathinal ◽  
...  

2021 ◽  
Author(s):  
Mirela T. Cazzolato ◽  
Lucas S. Rodrigues ◽  
Marcela X. Ribeiro ◽  
Marco A. Gutierrez ◽  
Caetano Traina Jr. ◽  
...  

With the COVID-19 pandemic, many hospitals have collected Electronic Health Records (EHRs) from patients and shared them publicly. EHRs include heterogeneous attribute types, such as image exams, numerical, textual, and categorical information. Simply posing similarity queries over EHRs can underestimate the semantics and potential information of particular attributes and thus would be best supported by exploratory data analysis methods. Thus, we propose the Sketch method for comparing EHRs by similarity to provide a tool for a correlation-based exploratory analysis over different attributes. Sketch computes the overall data correlation considering the distance space of every attribute. Further, it employs both ANOVA and association rules with lift correlations to study the relationship between variables, allowing a deep data analysis. As a case study, we employed two open databases of COVID-19 cases, showing that specialists can benefit from the inference modules of Sketch to analyze EHRs. Sketch found strong correlations among tuples and attributes, with statistically significant results. The exploratory analysis has shown to complement the similarity search task, identifying and evaluating patterns discovered from heterogeneous attributes.


Nativa ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 794
Author(s):  
Pompeu Paes Guimarães ◽  
Vinícius Gomes de Castro ◽  
Flavio Cipriano de Assis do Carmo ◽  
Nilton Cesar Fiedler ◽  
Renato César Gonçalves Robert ◽  
...  

O objetivo do artigo é analisar os empregos diretos e os acidentes de trabalho ocorridos na produção florestal, em plantadas, nativas e atividades de apoio. Para cada atividade, no período de 2006 a 2014, foi contabilizado o número de empregos diretos, acidentes totais, registrados, típicos, de trajeto e doenças do trabalho e os acidentes não registrados. Foram ajustados modelos de tendência para cálculo das taxas de crescimento anual dos empregos diretos e dos acidentes de trabalho. Foi utilizada a correlação linear de Pearson para explicar a relação entre o número de empregos diretos e os acidentes da produção florestal. O número de empregos diretos gerados na produção de plantadas e nativas aumentou nos últimos 8 anos. Apenas para o setor de atividades de apoio decresceu o quadro de trabalhadores. Dentre os acidentes contabilizados, as plantadas apresentaram, em média, o maior número de acidentes, seguidos pelas atividades de apoio e produção de nativas. Muitos acidentes ocorridos não são comunicados, dando prejuízos aos acidentados quanto à reivindicação de seus direitos. Dos acidentes registrados o principal tipo corresponde ao acidente típico. Fortes correlações foram encontradas entre os empregos diretos e os acidentes totais para as florestas plantadas e atividades de apoio.Palavras-chave: empregos diretos; acidentes; cadeia produtiva. FOREST PRODUCTION WORK SAFETY ABSTRACT: The objective of this paper is to analyze the direct employment and work accidents that occurred in forest production, in plantations, native and support activities. For each activity, in the period from 2006 to 2014, the number of direct jobs, total, registered, typical, commuting and work-related accidents and unrecorded accidents were recorded. Trend models were calculated for the calculation of the annual growth rates of direct jobs and work accidents. Pearson's linear correlation was used to explain the relationship between the number of direct jobs and the accidents of forestry production. The number of direct jobs generated in plantation and native production has increased over the past 8 years. Only for the sector of support activities has the workforce declined. Among the accidents recorded, the planted had, on average, the largest number of accidents, followed by activities of support and production of natives. Many accidents occurred are not communicated, giving damage to the injured in claiming their rights. Of the accidents recorded the main type corresponds to the typical accident. Strong correlations were found between direct jobs and total accidents for planted forests and support activities.Keywords: direct jobs; accidents; productive chain.


2015 ◽  
Vol 1 ◽  
pp. e33 ◽  
Author(s):  
Elisha D. Roberson

CRISPR/Cas9 is emerging as one of the most-used methods of genome modification in organisms ranging from bacteria to human cells. However, the efficiency of editing varies tremendously site-to-site. A recent report identified a novel motif, called the 3′GG motif, which substantially increases the efficiency of editing at all sites tested inC. elegans. Furthermore, they highlighted that previously published gRNAs with high editing efficiency also had this motif. I designed a Python command-line tool, ngg2, to identify 3′GG gRNA sites from indexed FASTA files. As a proof-of-concept, I screened for these motifs in six model genomes:Saccharomyces cerevisiae,Caenorhabditis elegans,Drosophila melanogaster,Danio rerio,Mus musculus, andHomo sapiens. I also scanned the genomes of pig (Sus scrofa) and African elephant (Loxodonta africana) to demonstrate the utility in non-model organisms. I identified more than 60 million single match 3′GG motifs in these genomes. Greater than 61% of all protein coding genes in the reference genomes had at least one unique 3′GG gRNA site overlapping an exon. In particular, more than 96% of mouse and 93% of human protein coding genes have at least one unique, overlapping 3′GG gRNA. These identified sites can be used as a starting point in gRNA selection, and the ngg2 tool provides an important ability to identify 3′GG editing sites in any species with an available genome sequence.


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