2,653 research outputs found
Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces
biological space
Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throughput RNAi screens
<p>Abstract</p> <p>Background</p> <p>The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the interpretation of cellular phenotypes in different experimental conditions has been dependent upon the expert opinions of well-trained biologists. Such qualitative analysis is particularly effective in detecting subtle, but important, deviations in phenotypes. However, while the rapid and continuing development of automated microscope-based technologies now facilitates the acquisition of trillions of cells in thousands of diverse experimental conditions, such as in the context of RNA interference (RNAi) or small-molecule screens, the massive size of these datasets precludes human analysis. Thus, the development of automated methods which aim to identify novel and biological relevant phenotypes online is one of the major challenges in high-throughput image-based screening. Ideally, phenotype discovery methods should be designed to utilize prior/existing information and tackle three challenging tasks, i.e. restoring pre-defined biological meaningful phenotypes, differentiating novel phenotypes from known ones and clarifying novel phenotypes from each other. Arbitrarily extracted information causes biased analysis, while combining the complete existing datasets with each new image is intractable in high-throughput screens.</p> <p>Results</p> <p>Here we present the design and implementation of a novel and robust online phenotype discovery method with broad applicability that can be used in diverse experimental contexts, especially high-throughput RNAi screens. This method features phenotype modelling and iterative cluster merging using improved gap statistics. A Gaussian Mixture Model (GMM) is employed to estimate the distribution of each existing phenotype, and then used as reference distribution in gap statistics. This method is broadly applicable to a number of different types of image-based datasets derived from a wide spectrum of experimental conditions and is suitable to adaptively process new images which are continuously added to existing datasets. Validations were carried out on different dataset, including published RNAi screening using <it>Drosophila </it>embryos [Additional files <supplr sid="S1">1</supplr>, <supplr sid="S2">2</supplr>], dataset for cell cycle phase identification using HeLa cells [Additional files <supplr sid="S1">1</supplr>, <supplr sid="S3">3</supplr>, <supplr sid="S4">4</supplr>] and synthetic dataset using polygons, our methods tackled three aforementioned tasks effectively with an accuracy range of 85%–90%. When our method is implemented in the context of a <it>Drosophila </it>genome-scale RNAi image-based screening of cultured cells aimed to identifying the contribution of individual genes towards the regulation of cell-shape, it efficiently discovers meaningful new phenotypes and provides novel biological insight. We also propose a two-step procedure to modify the novelty detection method based on one-class SVM, so that it can be used to online phenotype discovery. In different conditions, we compared the SVM based method with our method using various datasets and our methods consistently outperformed SVM based method in at least two of three tasks by 2% to 5%. These results demonstrate that our methods can be used to better identify novel phenotypes in image-based datasets from a wide range of conditions and organisms.</p> <p>Conclusion</p> <p>We demonstrate that our method can detect various novel phenotypes effectively in complex datasets. Experiment results also validate that our method performs consistently under different order of image input, variation of starting conditions including the number and composition of existing phenotypes, and dataset from different screens. In our findings, the proposed method is suitable for online phenotype discovery in diverse high-throughput image-based genetic and chemical screens.</p
Multiple-image encryption by compressive holography
We present multiple-image encryption (MIE) based on compressive holography. In the encryption, a holographic technique is employed to record multiple images simultaneously to form a hologram. The two-dimensional Fourier data of the hologram are then compressed by nonuniform sampling, which gives rise to compressive encryption. Decryption of individual images is cast into a minimization problem. The minimization retains the sparsity of recovered images in the wavelet basis. Meanwhile, total variation regularization is used to preserve edges in the reconstruction. Experiments have been conducted using holograms acquired by optical scanning holography as an example. Computer simulations of multiple images are subsequently demonstrated to illustrate the feasibility of the MIE scheme.published_or_final_versio
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102 fs pulse generation from a long-term stable, inkjet-printed black phosphorus-mode-locked fiber laser.
We demonstrate a long-term stable, all-fiber, erbium-doped femtosecond laser mode-locked by a black phosphorus saturable absorber. The saturable absorber, fabricated by scalable and highly controllable inkjet printing technology, exhibits strong nonlinear optical response and is stable for long-term operation against intense irradiation, overcoming a key drawback of this material. The oscillator delivers self-starting, 102 fs stable pulses centered at 1555 nm with 40 nm spectral bandwidth. This represents the shortest pulse duration achieved from black phosphorus in a fiber laser to date. Our results demonstrate the great potential for black phosphorus as an excellent candidate for long-term stable ultrashort pulse generation
GIVE: portable genome browsers for personal websites.
Growing popularity and diversity of genomic data demand portable and versatile genome browsers. Here, we present an open source programming library called GIVE that facilitates the creation of personalized genome browsers without requiring a system administrator. By inserting HTML tags, one can add to a personal webpage interactive visualization of multiple types of genomics data, including genome annotation, "linear" quantitative data, and genome interaction data. GIVE includes a graphical interface called HUG (HTML Universal Generator) that automatically generates HTML code for displaying user chosen data, which can be copy-pasted into user's personal website or saved and shared with collaborators. GIVE is available at: https://www.givengine.org/
Association of body mass index, metabolic health status and clinical outcomes in acute myocardial infarction patients: a national registry-based study
INTRODUCTION:
Obesity is an important risk factor for acute myocardial infarction (AMI), but the interplay between metabolic health and obesity on AMI mortality has been controversial. In this study, we aimed to elucidate the risk of short- and long-term all-cause mortality by obesity and metabolic health in AMI patients using data from a multi-ethnic national AMI registry.
METHODS:
A total of 73,382 AMI patients from the national Singapore Myocardial Infarction Registry (SMIR) were included. These patients were classified into four groups based on the presence or absence of metabolic diseases, diabetes mellitus, hyperlipidaemia, and hypertension, and obesity: (1) metabolically-healthy-normal-weight (MHN); (2) metabolically-healthy-obese (MHO); (3) metabolically-unhealthy-normal-weight (MUN); and (4) metabolically-unhealthy-obese (MUO).
RESULTS:
MHO patients had reduced unadjusted risk of all-cause in-hospital, 30-day, 1-year, 2-year, and 5-year mortality following the initial MI event. However, after adjusting for potential confounders, the protective effect from MHO on post-AMI mortality was lost. Furthermore, there was no reduced risk of recurrent MI or stroke within 1-year from onset of AMI by the MHO status. However, the risk of 1-year mortality was higher in female and Malay AMI patients with MHO compared to MHN even after adjusting for confounders.
CONCLUSION:
In AMI patients with or without metabolic diseases, the presence of obesity did not affect mortality. The exception to this finding were female and Malay MHO who had worse long-term AMI mortality outcomes when compared to MHN suggesting that the presence of obesity in female and Malay patients may confer worsened outcomes
Feature selection for chemical sensor arrays using mutual information
We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays
Investigation of glutathione S-transferase zeta and the development of sporadic breast cancer
BACKGROUND: Certain genes from the glutathione S-transferase superfamily have been associated with several cancer types. It was the objective of this study to determine whether alleles of the glutathione S-transferase zeta 1 (GSTZ1) gene are associated with the development of sporadic breast cancer. METHODS: DNA samples obtained from a Caucasian population affected by breast cancer and a control population, matched for age and ethnicity, were genotyped for a polymorphism of the GSTZ1 gene. After PCR, alleles were identified by restriction enzyme digestion and results analysed by chi-square and CLUMP analysis. RESULTS: Chi-squared analysis gave a χ(2) value of 4.77 (three degrees of freedom) with P = 0.19, and CLUMP analysis gave a T1 value of 9.02 with P = 0.45 for genotype frequencies and a T1 value of 4.77 with P = 0.19 for allele frequencies. CONCLUSION: Statistical analysis indicates that there is no association of the GSTZ1 variant and hence the gene does not appear to play a significant role in the development of sporadic breast cancer
An elitist quantum-inspired evolutionary algorithm for the flexible job-shop scheduling problem
The flexible job shop scheduling problem (FJSP) is vital to manufacturers especially in today’s constantly changing environment. It is a strongly NP-hard problem and therefore metaheuristics or heuristics are usually pursued to solve it. Most of the existing metaheuristics and heuristics, however, have low efficiency in convergence speed. To overcome this drawback, this paper develops an elitist quantum-inspired evolutionary algorithm. The algorithm aims to minimise the maximum completion time (makespan). It performs a global search with the quantum-inspired evolutionary algorithm and a local search with a method that is inspired by the motion mechanism of the electrons around an atomic nucleus. Three novel algorithms are proposed and their effect on the whole search is discussed. The elitist strategy is adopted to prevent the optimal solution from being destroyed during the evolutionary process. The results show that the proposed algorithm outperforms the best-known algorithms for FJSPs on most of the FJSP benchmarks
Multiple ITS Copies Reveal Extensive Hybridization within Rheum (Polygonaceae), a Genus That Has Undergone Rapid Radiation
During adaptive radiation events, characters can arise multiple times due to parallel evolution, but transfer of traits through hybridization provides an alternative explanation for the same character appearing in apparently non-sister lineages. The signature of hybridization can be detected in incongruence between phylogenies derived from different markers, or from the presence of two divergent versions of a nuclear marker such as ITS within one individual.In this study, we cloned and sequenced ITS regions for 30 species of the genus Rheum, and compared them with a cpDNA phylogeny. Seven species contained two divergent copies of ITS that resolved in different clades from one another in each case, indicating hybridization events too recent for concerted evolution to have homogenised the ITS sequences. Hybridization was also indicated in at least two further species via incongruence in their position between ITS and cpDNA phylogenies. None of the ITS sequences present in these nine species matched those detected in any other species, which provides tentative evidence against recent introgression as an explanation. Rheum globulosum, previously indicated by cpDNA to represent an independent origin of decumbent habit, is indicated by ITS to be part of clade of decumbent species, which acquired cpDNA of another clade via hybridization. However decumbent and glasshouse morphology are confirmed to have arisen three and two times, respectively.These findings suggested that hybridization among QTP species of Rheum has been extensive, and that a role of hybridization in diversification of Rheum requires investigation
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