The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The synergistic relationship between structure and the bulk properties of polyelectrolyte multilayer (PEM) films has generated tremendous interest in their application for loading and release of bioactive species. Layer-by-layer assembly is the simplest, cost effective process for fabrication of such PEMs films, leading to one of the most widely accepted platforms for incorporating biological molecules...
A large number of long non-coding RNAs (lncRNAs) have been identified over the past decades. Accumulating evidence proves that lncRNAs play key roles in various biological processes. However, the majority of the lncRNAs have not been functionally characterized. The annotation of lncRNA functions has become an area of focus in the fields of biology and bioinformatics. In this paper, we develop a global...
Alternative splicing (AS) produces multiple messenger RNAs by combining different regions of the precursor transcript to produce diversity in gene products. Under stress conditions, many genes produce transcripts that are not otherwise produced during normal conditions. Plant growth and development are extensively affected by environmental stresses. In this study, we combine Differentially Alternatively...
Differential gene expression analysis is one of the significant efforts in single cell RNA sequencing (scRNAseq) analysis to discover the specific changes in expression levels of individual cell types. Since scRNAseq exhibits multimodality, large amounts of zero counts, and sparsity, it is different from the traditional bulk RNA sequencing (RNAseq) data. The new challenges of scRNAseq data promote...
We present improved methodology for prediction of medium and large sized RNA three dimensional structures, based on comparative modeling approach. Method is enriched by the prediction of secondary structure, which is then used in tertiary structure prediction.
MicroRNA is a type of short non-coding RNAs, which post-transcriptionally regulate gene expressions. It has been well-documented that human microRNAs contribute in the disease development, such as cancers and obesity. While most microRNA functional studies heavily rely on the regulatory interactions between microRNAs and their target messenger RNAs, the accumulating evidence has shown that the altered...
Current analysis of tumor proliferation, the most salient breast cancer prognostic biomarker, is limited to subjective mitosis counting by pathologists in localized regions of tissue images. This study presents the first data-driven integrative approach to characterize the severity of tumor growth and spread on a categorical and molecular level, utilizing multiple biologically salient deep learning...
Identifying the interactions between proteins and Long non-coding RNAs (lncRNAs) can provide valuable clues for understanding the mechanisms and physiological functions of lncRNAs. In this work, we propose a computational method, PLIPCOM, which can accurately detect protein-lncRNA interactions by integrating two groups of network features. Low dimensional diffusion characteristics and HeteSim features...
MicroRNAs regulate virtually the whole gene network in human body and have been implicated in most physiological and pathological conditions including cancers. Understanding the precise mechanisms of microRNA-mRNA interaction is fundamentally important to elucidate the important roles of miRNA in regulating various cellular and disease developmental stages. Numerous computational methods have been...
With the development of deep sequencing technology, isomiRs (isoform of miRNA) are consistently observed in a variety of cell types, tissues, and different cell development stages. miRNA isoforms as the products of miRNA genes, are variants which are different from mature miRNAs in length and position. Recently, many studies emphasized on isomiR and found its subtypes are differentially expression...
Background: BCR-ABL1 fusion gene is the molecular hallmark of most cases of chronic myeloid leukaemia and some cases of acute lymphoblastic leukaemia. All CML cases that have Philadelphia chromosome, t (9; 22) (q34; q11) translocation express BCR-ABL1. For both diagnosis and minimal residual disease monitoring, Real Time PCR is used to quantify BCR-ABL1 in peripheral blood. However, messenger RNA...
Bacterial small non-coding RNAs (sRNAs) play important roles in various physiological processes, and predicting sRNAs is an important task. In this paper, we develop a computational method for the sRNA prediction by using sRNA sequence-derived features. We investigate a variety of sRNA sequence-derived features, and evaluate the usefulness of features for the sRNA prediction. Then, we develop the...
The dysregulations of long intergenic non-coding RNAs (lincRNAs) have shown to be linked with a wide variety of human diseases over the past few years. However, there are only a few lincRNA-disease association inference tools available with most of them relying on very specific type of prior knowledge about the lincRNAs and the diseases. They fall short in generalized association predictions when...
Gene Co-expression Network (GCN) analysis is a method to characterize the complexity underlying biological systems. With an increasing availability of datasets available for mining complex gene expression patterns, novel algorithms and computational frameworks must be developed to take advantage of the wealth of information. OSG-KINC is a Pegasus workflow that enables highly parallel execution of...
Marked drug-induced prolongation of the QT interval on the electrocardiogram is associated with Torsades de Pointes (TdP), a potentially life-threatening cardiac arrhythmia. Assessment of QT prolongation liability in the drug development process is required but is time and resource intensive. Current pre-clinical safety assessments use patch clamp analysis of the Human Ether-a-Go-Go (hERG) channel,...
Sequence alignment is a core step in the processing of DNA and RNA sequencing data. In this paper, we present a high performance GPU accelerated set of APIs (GASAL) for pairwise sequence alignment of DNA and RNA sequences. The GASAL APIs provide accelerated kernels for local, global as well as semi-global alignment, allowing the computation of the alignment score, and optionally the start and end...
We develop a cache-efficient RNA folding algorithm, ByBox, that is based on Zuker's method. Using a simple LRU cache model, we show that the traditional implementation, Zuker, of Zuker's method has a much higher number of cache misses than ByBox. Extensive experiments conducted on the Xeon E5 server show that cache efficiency translates into time and energy efficiency. Our benchmarking shows that,...
With the development of next-generation sequencing technologies, large number of transcripts has been accumulated in public databases. Long non-coding RNAs (lncRNAs), typically above 200 nucleotides in sequence length, have recently attracted increasing interests because of their important roles in various cellular processes. While it is straightforward to distinguishing lncRNAs from most small non-coding...
Although there are widely used methods as Genetic Algorithms, Fuzzy Logic and Artificial Neural Network, the Optimization Based Tools are considered the future of the systems of information. This issue is about Artificial Neural Network (ANN) used in Short Term Load Forecast (STLF). It proposes that the method is valid to predict STLF and how important it is on demand scheduling, contingency analysis,...
An application of artificial vision and artificial neural networks techniques in face recognition, is presented. In order to do that, a set of images (frontal face photos) with different lighting conditions, gestures, accessories and distances is used. A stepwise algorithm allows to achieve a satisfactory results, obtaining the correct identification of images inside and outside the data set.
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.