59 research outputs found

    Development and implementation of an algorithm for detection of protein complexes in large interaction networks

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    BACKGROUND: After complete sequencing of a number of genomes the focus has now turned to proteomics. Advanced proteomics technologies such as two-hybrid assay, mass spectrometry etc. are producing huge data sets of protein-protein interactions which can be portrayed as networks, and one of the burning issues is to find protein complexes in such networks. The enormous size of protein-protein interaction (PPI) networks warrants development of efficient computational methods for extraction of significant complexes. RESULTS: This paper presents an algorithm for detection of protein complexes in large interaction networks. In a PPI network, a node represents a protein and an edge represents an interaction. The input to the algorithm is the associated matrix of an interaction network and the outputs are protein complexes. The complexes are determined by way of finding clusters, i. e. the densely connected regions in the network. We also show and analyze some protein complexes generated by the proposed algorithm from typical PPI networks of Escherichia coli and Saccharomyces cerevisiae. A comparison between a PPI and a random network is also performed in the context of the proposed algorithm. CONCLUSION: The proposed algorithm makes it possible to detect clusters of proteins in PPI networks which mostly represent molecular biological functional units. Therefore, protein complexes determined solely based on interaction data can help us to predict the functions of proteins, and they are also useful to understand and explain certain biological processes

    MODELLING INGREDIENT OF JAMU TO PREDICT ITS EFFICACY

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    Jamu is an Indonesian herbal medicine made from a mixture of several plants.聽 Nowadays, many jamu are聽 produced commercially by many industries in Indonesia.聽 Each producer may have their own jamu formula. However, one is certain; the efficacy of jamu is determined by the composition of the plants used.聽 Thus, it is interesting to model the ingredient of jamu which consist of plants and use it to predict efficacy of jamu.聽 In this analysis, Partial Least Squares Discriminant Analysis (PLSDA) is used in modeling jamu ingredients to predict聽 the聽 efficacy.聽 It聽 is聽 obtained聽 that聽 utilizing the prediction of聽 y ij obtained聽 from聽 PLSDA聽 directly聽 rather聽 than聽 use聽 it聽 to calculate probability of jamu i belong to efficacy j and then use the probability to predict efficacy produces lower False Positive Rate (FPR) in predicting efficacy group. 聽Keywords: Jamu, PLSD

    The entire organization of transcription units on the Bacillus subtilis genome

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    <p>Abstract</p> <p>Background</p> <p>In the post-genomic era, comprehension of cellular processes and systems requires global and non-targeted approaches to handle vast amounts of biological information.</p> <p>Results</p> <p>The present study predicts transcription units (TUs) in <it>Bacillus subtilis</it>, based on an integrated approach involving DNA sequence and transcriptome analyses. First, co-expressed gene clusters are predicted by calculating the Pearson correlation coefficients of adjacent genes for all the genes in a series that are transcribed in the same direction with no intervening gene transcribed in the opposite direction. Transcription factor (TF) binding sites are then predicted by detecting statistically significant TF binding sequences on the genome using a position weight matrix. This matrix is a convenient way to identify sites that are more highly conserved than others in the entire genome because any sequence that differs from a consensus sequence has a lower score. We identify genes regulated by each of the TFs by comparing gene expression between wild-type and TF mutants using a one-sided test. By applying the integrated approach to 11 蟽 factors and 17 TFs of <it>B. subtilis</it>, we are able to identify fewer candidates for genes regulated by the TFs than were identified using any single approach, and also detect the known TUs efficiently.</p> <p>Conclusion</p> <p>This integrated approach is, therefore, an efficient tool for narrowing searches for candidate genes regulated by TFs, identifying TUs, and estimating roles of the 蟽 factors and TFs in cellular processes and functions of genes composing the TUs.</p

    Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry

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    Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR/MS) is the best MS technology for obtaining exact mass measurements owing to its great resolution and accuracy, and several outstanding FT-ICR/MS-based metabolomics approaches have been reported. A reliable annotation scheme is needed to deal with direct-infusion FT-ICR/MS metabolic profiling. Correlation analyses can help us not only uncover relations between the ions but also annotate the ions originated from identical metabolites (metabolite derivative ions). In the present study, we propose a procedure for metabolite annotation on direct-infusion FT-ICR/MS by taking into consideration the classification of metabolite-derived ions using correlation analyses. Integrated analysis based on information of isotope relations, fragmentation patterns by MS/MS analysis, co-occurring metabolites, and database searches (KNApSAcK and KEGG) can make it possible to annotate ions as metabolites and estimate cellular conditions based on metabolite composition. A total of 220 detected ions were classified into 174 metabolite derivative groups and 72 ions were assigned to candidate metabolites in the present work. Finally, metabolic profiling has been able to distinguish between the growth stages with the aid of PCA. The constructed model using PLS regression for OD600 values as a function of metabolic profiles is very useful for identifying to what degree the ions contribute to the growth stages. Ten phospholipids which largely influence the constructed model are highly abundant in the cells. Our analyses reveal that global modification of those phospholipids occurs as E. coli enters the stationary phase. Thus, the integrated approach involving correlation analyses, metabolic profiling, and database searching is efficient for high-throughput metabolomics

    Sequence-specific error profile of Illumina sequencers

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    We identified the sequence-specific starting positions of consecutive miscalls in the mapping of reads obtained from the Illumina Genome Analyser (GA). Detailed analysis of the miscall pattern indicated that the underlying mechanism involves sequence-specific interference of the base elongation process during sequencing. The two major sequence patterns that trigger this sequence-specific error (SSE) are: (i) inverted repeats and (ii) GGC sequences. We speculate that these sequences favor dephasing by inhibiting single-base elongation, by: (i) folding single-stranded DNA and (ii) altering enzyme preference. This phenomenon is a major cause of sequence coverage variability and of the unfavorable bias observed for population-targeted methods such as RNA-seq and ChIP-seq. Moreover, SSE is a potential cause of false single-nucleotide polymorphism (SNP) calls and also significantly hinders de novo assembly. This article highlights the importance of recognizing SSE and its underlying mechanisms in the hope of enhancing the potential usefulness of the Illumina sequencers

    Global variation in anastomosis and end colostomy formation following left-sided colorectal resection

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    Background End colostomy rates following colorectal resection vary across institutions in high-income settings, being influenced by patient, disease, surgeon and system factors. This study aimed to assess global variation in end colostomy rates after left-sided colorectal resection. Methods This study comprised an analysis of GlobalSurg-1 and -2 international, prospective, observational cohort studies (2014, 2016), including consecutive adult patients undergoing elective or emergency left-sided colorectal resection within discrete 2-week windows. Countries were grouped into high-, middle- and low-income tertiles according to the United Nations Human Development Index (HDI). Factors associated with colostomy formation versus primary anastomosis were explored using a multilevel, multivariable logistic regression model. Results In total, 1635 patients from 242 hospitals in 57 countries undergoing left-sided colorectal resection were included: 113 (6路9 per cent) from low-HDI, 254 (15路5 per cent) from middle-HDI and 1268 (77路6 per cent) from high-HDI countries. There was a higher proportion of patients with perforated disease (57路5, 40路9 and 35路4 per cent; P < 0路001) and subsequent use of end colostomy (52路2, 24路8 and 18路9 per cent; P < 0路001) in low- compared with middle- and high-HDI settings. The association with colostomy use in low-HDI settings persisted (odds ratio (OR) 3路20, 95 per cent c.i. 1路35 to 7路57; P = 0路008) after risk adjustment for malignant disease (OR 2路34, 1路65 to 3路32; P < 0路001), emergency surgery (OR 4路08, 2路73 to 6路10; P < 0路001), time to operation at least 48 h (OR 1路99, 1路28 to 3路09; P = 0路002) and disease perforation (OR 4路00, 2路81 to 5路69; P < 0路001). Conclusion Global differences existed in the proportion of patients receiving end stomas after left-sided colorectal resection based on income, which went beyond case mix alone

    Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries