Search results for "Complexity"
showing 10 items of 1094 documents
Development of an RNA-based kit for easy generation of TCR-engineered lymphocytes to control T-cell assay performance.
2018
Cell-based assays to monitor antigen-specific T-cell responses are characterized by their high complexity and should be conducted under controlled conditions to lower multiple possible sources of assay variation. However, the lack of standard reagents makes it difficult to directly compare results generated in one lab over time and across institutions. Therefore TCR-engineered reference samples (TERS) that contain a defined number of antigen-specific T cells and continuously deliver stable results are urgently needed. We successfully established a simple and robust TERS technology that constitutes a useful tool to overcome this issue for commonly used T-cell immuno-assays. To enable users t…
A Novel Tsetlin Automata Scheme to Forecast Dengue Outbreaks in the Philippines
2018
Being capable of online learning in unknown stochastic environments, Tsetlin Automata (TA) have gained considerable interest. As a model of biological systems, teams of TA have been used for solving complex problems in a decentralized manner, with low computational complexity. For many domains, decentralized problem solving is an advantage, however, also may lead to coordination difficulties and unstable learning. To combat this negative effect, this paper proposes a novel TA coordination scheme designed for learning problems with continuous input and output. By saving and updating the best solution that has been chosen so far, we can avoid having the overall system being led astray by spur…
Ultra-Fast Detection of Higher-Order Epistatic Interactions on GPUs
2017
Detecting higher-order epistatic interactions in Genome-Wide Association Studies (GWAS) remains a challenging task in the fields of genetic epidemiology and computer science. A number of algorithms have recently been proposed for epistasis discovery. However, they suffer from a high computational cost since statistical measures have to be evaluated for each possible combination of markers. Hence, many algorithms use additional filtering stages discarding potentially non-interacting markers in order to reduce the overall number of combinations to be examined. Among others, Mutual Information Clustering (MIC) is a common pre-processing filter for grouping markers into partitions using K-Means…
An Integrative Framework for the Construction of Big Functional Networks
2018
We present a methodology for biological data integration, aiming at building and analysing large functional networks which model complex genotype-phenotype associations. A functional network is a graph where nodes represent cellular components (e.g., genes, proteins, mRNA, etc.) and edges represent associations among such molecules. Different types of components may cohesist in the same network, and associations may be related to physical[biochemical interactions or functional/phenotipic relationships. Due to both the large amount of involved information and the computational complexity typical of the problems in this domain, the proposed framework is based on big data technologies (Spark a…
Chemical messages from an ancient buried bottle: Metabolomics for wine archeochemistry.
2017
Restoration works in the old Clunisian Saint-Vivant monastery in Burgundy revealed an unidentified wine bottle (SV1) dating between 1772 and 1860. Chemical evidence for SV1 origin and nature are presented here using non-targeted Fourier Transform Ion Cyclotron Resonance Mass Spectrometry and Nuclear Magnetic Resonance analyses. The SV1 chemical diversity was compared to red wines (Pinot Noir) from the Romanée Saint Vivant appellation and from six different vintages spanning from 1915 to 2009. The close metabolomic signature between SV1 and Romanée Saint Vivant wines spoke in favor of a filiation between these wines, in particular considering the Pinot noir grape variety. A further statistic…
Generation of TCR-engineered reference cell samples to control T-cell assay performance
2020
In vitro cellular assays analyzing antigen-specific T cells are characterized by their high complexity and require controlled conditions to lower experimental variations. Without standard cellular reagents, it is difficult to compare results over time and across institutions. To overcome this problem, a simple and robust technology was developed to generate TCR-engineered reference samples (TERS) containing defined numbers of antigen-specific T cells. Utilization of TERS enables performance control of three main T-cell assays: MHC-peptide multimer staining, IFN-gamma ELISpot and cytokine flow cytometry. TERS continuously deliver stable results and can be stored for longer periods of time. H…
Numerical Study on the Heading Misalignment and Current Velocity Reduction of a Vessel-Shaped Offshore Fish Farm
2019
Recently, the concept of a vessel-shaped fish farm was proposed for open sea applications. The fish farm comprises a vessel-shaped floater, five fish cages, and a single-point mooring system. Such a system weathervanes, and this feature increases the spread area of fish waste. Still, the downstream cages may experience decreased exchange of water flow when the vessel heading is aligned with the current direction, and fish welfare may be jeopardized. To ameliorate the flow conditions, a dynamic positioning (DP) system may be required, and its power consumption should relate to the heading misalignment. This paper proposes an integrated method for predicting the heading misalignment between t…
DNA combinatorial messages and Epigenomics: The case of chromatin organization and nucleosome occupancy in eukaryotic genomes
2019
Abstract Epigenomics is the study of modifications on the genetic material of a cell that do not depend on changes in the DNA sequence, since those latter involve specific proteins around which DNA wraps. The end result is that Epigenomic changes have a fundamental role in the proper working of each cell in Eukaryotic organisms. A particularly important part of Epigenomics concentrates on the study of chromatin, that is, a fiber composed of a DNA-protein complex and very characterizing of Eukaryotes. Understanding how chromatin is assembled and how it changes is fundamental for Biology. In more than thirty years of research in this area, Mathematics and Theoretical Computer Science have gai…
Dynamic Functional Connectivity Captures Individuals’ Unique Brain Signatures
2020
Recent neuroimaging evidence suggest that there exists a unique individual-specific functional connectivity (FC) pattern consistent across tasks. The objective of our study is to utilize FC patterns to identify an individual using a supervised machine learning approach. To this end, we use two previously published data sets that comprises resting-state and task-based fMRI responses. We use static FC measures as input to a linear classifier to evaluate its performance. We additionally extend this analysis to capture dynamic FC using two approaches: the common sliding window approach and the more recent phase synchrony-based measure. We found that the classification models using dynamic FC pa…
Attention-based Model for Evaluating the Complexity of Sentences in English Language
2020
The automation of text complexity evaluation (ATCE) is an emerging problem which has been tackled by means of different methodologies. We present an effective deep learning- based solution which leverages both Recurrent Neural and the Attention mechanism. The developed system is capable of classifying sentences written in the English language by analysing their syntactical and lexical complexity. An accurate test phase has been carried out, and the system has been compared with a baseline tool based on the Support Vector Machine. This paper represents an extension of a previous deep learning model, which allows showing the suitability of Neural Networks to evaluate sentence complexity in tw…