Source Code for Biology and Medicine最新文献

{"title":"Symmetrical treatment of \"Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition\", for major depressive disorders.","authors":"Jitsuki Sawamura, Shigeru Morishita, Jun Ishigooka","doi":"10.1186/s13029-015-0041-7","DOIUrl":"10.1186/s13029-015-0041-7","url":null,"abstract":"<p><strong>Background: </strong>We previously presented a group theoretical model that describes psychiatric patient states or clinical data in a graded vector-like format based on modulo groups. Meanwhile, the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5, the current version), is frequently used for diagnosis in daily psychiatric treatments and biological research. The diagnostic criteria of DSM-5 contain simple binominal items relating to the presence or absence of specific symptoms. In spite of its simple form, the practical structure of the DSM-5 system is not sufficiently systemized for data to be treated in a more rationally sophisticated way. To view the disease states in terms of symmetry in the manner of abstract algebra is considered important for the future systematization of clinical medicine.</p><p><strong>Results: </strong>We provide a simple idea for the practical treatment of the psychiatric diagnosis/score of DSM-5 using depressive symptoms in line with our previously proposed method. An expression is given employing modulo-2 and -7 arithmetic (in particular, additive group theory) for Criterion A of a 'major depressive episode' that must be met for the diagnosis of 'major depressive disorder' in DSM-5. For this purpose, the novel concept of an imaginary value 0 that can be recognized as an explicit 0 or implicit 0 was introduced to compose the model. The zeros allow the incorporation or deletion of an item between any other symptoms if they are ordered appropriately. Optionally, a vector-like expression can be used to rate/select only specific items when modifying the criterion/scale. Simple examples are illustrated concretely.</p><p><strong>Conclusions: </strong>Further development of the proposed method for the criteria/scale of a disease is expected to raise the level of formalism of clinical medicine to that of other fields of natural science.</p>","PeriodicalId":35052,"journal":{"name":"Source Code for Biology and Medicine","volume":"11 1","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2016-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4717580/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65752802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PageRank as a method to rank biomedical literature by importance","authors":"E. J. Yates, Louise C. Dixon","doi":"10.1186/s13029-015-0046-2","DOIUrl":"https://doi.org/10.1186/s13029-015-0046-2","url":null,"abstract":"","PeriodicalId":35052,"journal":{"name":"Source Code for Biology and Medicine","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13029-015-0046-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65752914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PROPER: Performance visualization for optimizing and comparing ranking classifiers in MATLAB","authors":"S. Jahandideh, F. Sharifi, L. Jaroszewski, A. Godzik","doi":"10.1186/s13029-015-0047-1","DOIUrl":"https://doi.org/10.1186/s13029-015-0047-1","url":null,"abstract":"","PeriodicalId":35052,"journal":{"name":"Source Code for Biology and Medicine","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13029-015-0047-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65752464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PyPedia: using the wiki paradigm as crowd sourcing environment for bioinformatics protocols","authors":"A. Kanterakis, J. Kuiper, G. Potamias, M. Swertz","doi":"10.1186/s13029-015-0042-6","DOIUrl":"https://doi.org/10.1186/s13029-015-0042-6","url":null,"abstract":"","PeriodicalId":35052,"journal":{"name":"Source Code for Biology and Medicine","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13029-015-0042-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65752836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FlexDM: Simple, parallel and fault-tolerant data mining using WEKA","authors":"Madison Flannery, D. Budden, Alexandre Mendes","doi":"10.1186/s13029-015-0045-3","DOIUrl":"https://doi.org/10.1186/s13029-015-0045-3","url":null,"abstract":"","PeriodicalId":35052,"journal":{"name":"Source Code for Biology and Medicine","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13029-015-0045-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65752869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation.","authors":"Alice Mantoan, Claudio Pizzolato, Massimo Sartori, Zimi Sawacha, Claudio Cobelli, Monica Reggiani","doi":"10.1186/s13029-015-0044-4","DOIUrl":"10.1186/s13029-015-0044-4","url":null,"abstract":"<p><strong>Background: </strong>Neuromusculoskeletal modeling and simulation enable investigation of the neuromusculoskeletal system and its role in human movement dynamics. These methods are progressively introduced into daily clinical practice. However, a major factor limiting this translation is the lack of robust tools for the pre-processing of experimental movement data for their use in neuromusculoskeletal modeling software.</p><p><strong>Results: </strong>This paper presents MOtoNMS (matlab MOtion data elaboration TOolbox for NeuroMusculoSkeletal applications), a toolbox freely available to the community, that aims to fill this lack. MOtoNMS processes experimental data from different motion analysis devices and generates input data for neuromusculoskeletal modeling and simulation software, such as OpenSim and CEINMS (Calibrated EMG-Informed NMS Modelling Toolbox). MOtoNMS implements commonly required processing steps and its generic architecture simplifies the integration of new user-defined processing components. MOtoNMS allows users to setup their laboratory configurations and processing procedures through user-friendly graphical interfaces, without requiring advanced computer skills. Finally, configuration choices can be stored enabling the full reproduction of the processing steps. MOtoNMS is released under GNU General Public License and it is available at the SimTK website and from the GitHub repository. Motion data collected at four institutions demonstrate that, despite differences in laboratory instrumentation and procedures, MOtoNMS succeeds in processing data and producing consistent inputs for OpenSim and CEINMS.</p><p><strong>Conclusions: </strong>MOtoNMS fills the gap between motion analysis and neuromusculoskeletal modeling and simulation. Its support to several devices, a complete implementation of the pre-processing procedures, its simple extensibility, the available user interfaces, and its free availability can boost the translation of neuromusculoskeletal methods in daily and clinical practice.</p>","PeriodicalId":35052,"journal":{"name":"Source Code for Biology and Medicine","volume":"10 1","pages":"12"},"PeriodicalIF":0.0,"publicationDate":"2015-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4647340/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65752858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CyNetworkBMA: a Cytoscape app for inferring gene regulatory networks","authors":"Maciej Fronczuk, A. Raftery, K. Y. Yeung","doi":"10.1186/s13029-015-0043-5","DOIUrl":"https://doi.org/10.1186/s13029-015-0043-5","url":null,"abstract":"","PeriodicalId":35052,"journal":{"name":"Source Code for Biology and Medicine","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13029-015-0043-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65752849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TRX-LOGOS - a graphical tool to demonstrate DNA information content dependent upon backbone dynamics in addition to base sequence.","authors":"Connor H Fortin,&nbsp;Katharina V Schulze,&nbsp;Gregory A Babbitt","doi":"10.1186/s13029-015-0040-8","DOIUrl":"https://doi.org/10.1186/s13029-015-0040-8","url":null,"abstract":"<p><strong>Background: </strong>It is now widely-accepted that DNA sequences defining DNA-protein interactions functionally depend upon local biophysical features of DNA backbone that are important in defining sites of binding interaction in the genome (e.g. DNA shape, charge and intrinsic dynamics). However, these physical features of DNA polymer are not directly apparent when analyzing and viewing Shannon information content calculated at single nucleobases in a traditional sequence logo plot. Thus, sequence logos plots are severely limited in that they convey no explicit information regarding the structural dynamics of DNA backbone, a feature often critical to binding specificity.</p><p><strong>Software and implementation: </strong>We present TRX-LOGOS, an R software package and Perl wrapper code that interfaces the JASPAR database for computational regulatory genomics. TRX-LOGOS extends the traditional sequence logo plot to include Shannon information content calculated with regard to the dinucleotide-based BI-BII conformation shifts in phosphate linkages on the DNA backbone, thereby adding a visual measure of intrinsic DNA flexibility that can be critical for many DNA-protein interactions. TRX-LOGOS is available as an R graphics module offered at both SourceForge and as a download supplement at this journal.</p><p><strong>Results: </strong>To demonstrate the general utility of TRX logo plots, we first calculated the information content for 416 Saccharomyces cerevisiae transcription factor binding sites functionally confirmed in the Yeastract database and matched to previously published yeast genomic alignments. We discovered that flanking regions contain significantly elevated information content at phosphate linkages than can be observed at nucleobases. We also examined broader transcription factor classifications defined by the JASPAR database, and discovered that many general signatures of transcription factor binding are locally more information rich at the level of DNA backbone dynamics than nucleobase sequence. We used TRX-logos in combination with MEGA 6.0 software for molecular evolutionary genetics analysis to visually compare the human Forkhead box/FOX protein evolution to its binding site evolution. We also compared the DNA binding signatures of human TP53 tumor suppressor determined by two different laboratory methods (SELEX and ChIP-seq). Further analysis of the entire yeast genome, center aligned at the start codon, also revealed a distinct sequence-independent 3 bp periodic pattern in information content, present only in coding region, and perhaps indicative of the non-random organization of the genetic code.</p><p><strong>Conclusion: </strong>TRX-LOGOS is useful in any situation in which important information content in DNA can be better visualized at the positions of phosphate linkages (i.e. dinucleotides) where the dynamic properties of the DNA backbone functions to facilitate DNA-protein interaction.</p>","PeriodicalId":35052,"journal":{"name":"Source Code for Biology and Medicine","volume":"10 ","pages":"10"},"PeriodicalIF":0.0,"publicationDate":"2015-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13029-015-0040-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34211829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CombAlign: a code for generating a one-to-many sequence alignment from a set of pairwise structure-based sequence alignments.","authors":"Carol L Ecale Zhou","doi":"10.1186/s13029-015-0039-1","DOIUrl":"https://doi.org/10.1186/s13029-015-0039-1","url":null,"abstract":"<p><strong>Background: </strong>In order to better define regions of similarity among related protein structures, it is useful to identify the residue-residue correspondences among proteins. Few codes exist for constructing a one-to-many multiple sequence alignment derived from a set of structure or sequence alignments, and a need was evident for creating such a tool for combining pairwise structure alignments that would allow for insertion of gaps in the reference structure.</p><p><strong>Results: </strong>This report describes a new Python code, CombAlign, which takes as input a set of pairwise sequence alignments (which may be structure based) and generates a one-to-many, gapped, multiple structure- or sequence-based sequence alignment (MSSA). The use and utility of CombAlign was demonstrated by generating gapped MSSAs using sets of pairwise structure-based sequence alignments between structure models of the matrix protein (VP40) and pre-small/secreted glycoprotein (sGP) of Reston Ebolavirus and the corresponding proteins of several other filoviruses. The gapped MSSAs revealed structure-based residue-residue correspondences, which enabled identification of structurally similar versus differing regions in the Reston proteins compared to each of the other corresponding proteins.</p><p><strong>Conclusions: </strong>CombAlign is a new Python code that generates a one-to-many, gapped, multiple structure- or sequence-based sequence alignment (MSSA) given a set of pairwise sequence alignments (which may be structure based). CombAlign has utility in assisting the user in distinguishing structurally conserved versus divergent regions on a reference protein structure relative to other closely related proteins. CombAlign was developed in Python 2.6, and the source code is available for download from the GitHub code repository.</p>","PeriodicalId":35052,"journal":{"name":"Source Code for Biology and Medicine","volume":"10 ","pages":"9"},"PeriodicalIF":0.0,"publicationDate":"2015-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13029-015-0039-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33900388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PrimerView: high-throughput primer design and visualization.","authors":"Damien M O'Halloran","doi":"10.1186/s13029-015-0038-2","DOIUrl":"https://doi.org/10.1186/s13029-015-0038-2","url":null,"abstract":"<p><strong>Background: </strong>High-throughput primer design is routinely performed in a wide number of molecular applications including genotyping specimens using traditional PCR techniques as well as assembly PCR, nested PCR, and primer walking experiments. Batch primer design is also required in validation experiments from RNA-seq transcriptome sequencing projects, as well as in generating probes for microarray experiments. The growing popularity of next generation sequencing and microarray technology has created a greater need for more primer design tools to validate large numbers of candidate genes and markers.</p><p><strong>Results: </strong>To meet these demands I here present a tool called PrimerView that designs forward and reverse primers from multi-sequence datasets, and generates graphical outputs that map the position and distribution of primers to the target sequence. This module operates from the command-line and can collect user-defined input for the design phase of each primer.</p><p><strong>Conclusions: </strong>PrimerView is a straightforward to use module that implements a primer design algorithm to return forward and reverse primers from any number of FASTA formatted sequences to generate text based output of the features for each primer, and also graphical outputs that map the designed primers to the target sequence. PrimerView is freely available without restrictions.</p>","PeriodicalId":35052,"journal":{"name":"Source Code for Biology and Medicine","volume":"10 ","pages":"8"},"PeriodicalIF":0.0,"publicationDate":"2015-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13029-015-0038-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33367428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}