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Biological machines

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https://www.readbyqxmd.com/read/28107672/a-computational-model-of-conditioning-inspired-by-drosophila-olfactory-system
#1
Faramarz Faghihi, Ahmed A Moustafa, Ralf Heinrich, Florentin Wörgötter
Recent studies have demonstrated that Drosophila melanogaster (briefly Drosophila) can successfully perform higher cognitive processes including second order olfactory conditioning. Understanding the neural mechanism of this behavior can help neuroscientists to unravel the principles of information processing in complex neural systems (e.g. the human brain) and to create efficient and robust robotic systems. In this work, we have developed a biologically-inspired spiking neural network which is able to execute both first and second order conditioning...
November 23, 2016: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28107365/parenclitic-network-analysis-of-methylation-data-for-cancer-identification
#2
Alexander Karsakov, Thomas Bartlett, Artem Ryblov, Iosif Meyerov, Mikhail Ivanchenko, Alexey Zaikin
We make use of ideas from the theory of complex networks to implement a machine learning classification of human DNA methylation data, that carry signatures of cancer development. The data were obtained from patients with various kinds of cancers and represented as parenclictic networks, wherein nodes correspond to genes, and edges are weighted according to pairwise variation from control group subjects. We demonstrate that for the 10 types of cancer under study, it is possible to obtain a high performance of binary classification between cancer-positive and negative samples based on network measures...
2017: PloS One
https://www.readbyqxmd.com/read/28105918/mirnacle-machine-learning-with-smote-and-random-forest-for-improving-selectivity-in-pre-mirna-ab-initio-prediction
#3
Yuri Bento Marques, Alcione de Paiva Oliveira, Ana Tereza Ribeiro Vasconcelos, Fabio Ribeiro Cerqueira
BACKGROUND: MicroRNAs (miRNAs) are key gene expression regulators in plants and animals. Therefore, miRNAs are involved in several biological processes, making the study of these molecules one of the most relevant topics of molecular biology nowadays. However, characterizing miRNAs in vivo is still a complex task. As a consequence, in silico methods have been developed to predict miRNA loci. A common ab initio strategy to find miRNAs in genomic data is to search for sequences that can fold into the typical hairpin structure of miRNA precursors (pre-miRNAs)...
December 15, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/28105910/selected-proceedings-of-machine-learning-in-systems-biology-mlsb-2016
#4
Aalt D J van Dijk, Harri Lähdesmäki, Dick de Ridder, Juho Rousu
No abstract text is available yet for this article.
December 13, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/28102269/from-morphogen-to-morphogenesis-and-back
#5
Darren Gilmour, Martina Rembold, Maria Leptin
A long-term aim of the life sciences is to understand how organismal shape is encoded by the genome. An important challenge is to identify mechanistic links between the genes that control cell-fate decisions and the cellular machines that generate shape, therefore closing the gap between genotype and phenotype. The logic and mechanisms that integrate these different levels of shape control are beginning to be described, and recently discovered mechanisms of cross-talk and feedback are beginning to explain the remarkable robustness of organ assembly...
January 18, 2017: Nature
https://www.readbyqxmd.com/read/28098823/integrative-mirna-gene-expression-analysis-enables-refinement-of-associated-biology-and-prediction-of-response-to-cetuximab-in-head-and-neck-squamous-cell-cancer
#6
Loris De Cecco, Marco Giannoccaro, Edoardo Marchesi, Paolo Bossi, Federica Favales, Laura D Locati, Lisa Licitra, Silvana Pilotti, Silvana Canevari
This paper documents the process by which we, through gene and miRNA expression profiling of the same samples of head and neck squamous cell carcinomas (HNSCC) and an integrative miRNA-mRNA expression analysis, were able to identify candidate biomarkers of progression-free survival (PFS) in patients treated with cetuximab-based approaches. Through sparse partial least square-discriminant analysis (sPLS-DA) and supervised analysis, 36 miRNAs were identified in two components that clearly separated long- and short-PFS patients...
January 14, 2017: Genes
https://www.readbyqxmd.com/read/28097060/why-choose-random-forest-to-predict-rare-species-distribution-with-few-samples-in-large-undersampled-areas-three-asian-crane-species-models-provide-supporting-evidence
#7
Chunrong Mi, Falk Huettmann, Yumin Guo, Xuesong Han, Lijia Wen
Species distribution models (SDMs) have become an essential tool in ecology, biogeography, evolution and, more recently, in conservation biology. How to generalize species distributions in large undersampled areas, especially with few samples, is a fundamental issue of SDMs. In order to explore this issue, we used the best available presence records for the Hooded Crane (Grus monacha, n = 33), White-naped Crane (Grus vipio, n = 40), and Black-necked Crane (Grus nigricollis, n = 75) in China as three case studies, employing four powerful and commonly used machine learning algorithms to map the breeding distributions of the three species: TreeNet (Stochastic Gradient Boosting, Boosted Regression Tree Model), Random Forest, CART (Classification and Regression Tree) and Maxent (Maximum Entropy Models)...
2017: PeerJ
https://www.readbyqxmd.com/read/28095951/simulated-microgravity-effects-on-nonsmall-cell-lung-cancer-cell-proliferation-and-migration
#8
Jae Ho Chung, Chi Bum Ahn, Kuk Hui Son, Eunjue Yi, Ho Sung Son, Han-Sung Kim, Sung Ho Lee
BACKGROUND: Despite improvements in medical technology, lung cancer metastasis remains a global health problem. The effects of microgravity on cell morphology, structure, functions, and their mechanisms have been widely studied; however, the biological effects of simulated microgravity on the interaction between cells and its eventual influence on the characteristics of cancer cells are yet to be discovered. We examined the effects of simulated microgravity on the metastatic ability of different lung cancer cells using a random positioning machine...
February 1, 2017: Aerospace Medicine and Human Performance
https://www.readbyqxmd.com/read/28095660/draft-genome-of-toxocara-canis-a-pathogen-responsible-for-visceral-larva-migrans
#9
Jinhwa Kong, Jungim Won, Jeehee Yoon, UnJoo Lee, Jong-Il Kim, Sun Huh
This study aimed at constructing a draft genome of the adult female worm Toxocara canis using next-generation sequencing (NGS) and de novo assembly, as well as to find new genes after annotation using functional genomics tools. Using an NGS machine, we produced DNA read data of T. canis. The de novo assembly of the read data was performed using SOAPdenovo. RNA read data were assembled using Trinity. Structural annotation, homology search, functional annotation, classification of protein domains, and KEGG pathway analysis were carried out...
December 2016: Korean Journal of Parasitology
https://www.readbyqxmd.com/read/28092029/an-efficient-semi-supervised-learning-approach-to-predict-sh2-domain-mediated-interactions
#10
Kousik Kundu, Rolf Backofen
Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to facilitate various molecular functions. For determining the subtle binding specificities of SH2 domains, it is very important to understand the intriguing mechanisms by which these domains recognize their target peptides in a complex cellular environment. There are several attempts have been made to predict SH2-peptide interactions using high-throughput data...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28092028/sh2-ligand-prediction-guidance-for-in-silico-screening
#11
Shawn S C Li, Lei Li
Systematic identification of binding partners for SH2 domains is important for understanding the biological function of the corresponding SH2 domain-containing proteins. Here, we describe two different web-accessible computer programs, SMALI and DomPep, for predicting binding ligands for SH2 domains. The former was developed using a Scoring Matrix method and the latter based on the Support Vector Machine model.
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28088356/advancing-the-prediction-accuracy-of-protein-protein-interactions-by-utilizing-evolutionary-information-from-position-specific-scoring-matrix-and-ensemble-classifier
#12
Lei Wang, Zhu-Hong You, Shi-Xiong Xia, Feng Liu, Xing Chen, Xin Yan, Yong Zhou
Protein-Protein Interactions (PPIs) are essential to most biological processes and play a critical role in most cellular functions. With the development of high-throughput biological techniques and in silico methods, a large number of PPI data have been generated for various organisms, but many problems remain unsolved. These factors promoted the development of the in silico methods based on machine learning to predict PPIs. In this study, we propose a novel method by combining ensemble Rotation Forest (RF) classifier and Discrete Cosine Transform (DCT) algorithm to predict the interactions among proteins...
January 11, 2017: Journal of Theoretical Biology
https://www.readbyqxmd.com/read/28079187/a-spiking-neural-network-model-of-3d-perception-for-event-based-neuromorphic-stereo-vision-systems
#13
Marc Osswald, Sio-Hoi Ieng, Ryad Benosman, Giacomo Indiveri
Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain...
January 12, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28079126/detecting-n-6-methyladenosine-sites-from-rna-transcriptomes-using-ensemble-support-vector-machines
#14
Wei Chen, Pengwei Xing, Quan Zou
As one of the most abundant RNA post-transcriptional modifications, N(6)-methyladenosine (m(6)A) involves in a broad spectrum of biological and physiological processes ranging from mRNA splicing and stability to cell differentiation and reprogramming. However, experimental identification of m(6)A sites is expensive and laborious. Therefore, it is urgent to develop computational methods for reliable prediction of m(6)A sites from primary RNA sequences. In the current study, a new method called RAM-ESVM was developed for detecting m(6)A sites from Saccharomyces cerevisiae transcriptome, which employed ensemble support vector machine classifiers and novel sequence features...
January 12, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28077404/high-throughput-sequencing-of-the-t-cell-receptor-repertoire-pitfalls-and-opportunities
#15
James M Heather, Mazlina Ismail, Theres Oakes, Benny Chain
T-cell specificity is determined by the T-cell receptor, a heterodimeric protein coded for by an extremely diverse set of genes produced by imprecise somatic gene recombination. Massively parallel high-throughput sequencing allows millions of different T-cell receptor genes to be characterized from a single sample of blood or tissue. However, the extraordinary heterogeneity of the immune repertoire poses significant challenges for subsequent analysis of the data. We outline the major steps in processing of repertoire data, considering low-level processing of raw sequence files and high-level algorithms, which seek to extract biological or pathological information...
January 10, 2017: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/28070322/carotenoid-profiling-of-the-leaves-of-selected-african-eggplant-accessions-subjected-to-drought-stress
#16
Elias K Mibei, Jane Ambuko, James J Giovannoni, Arnold N Onyango, Willis O Owino
African eggplants (Solanum aethiopicum and S. macrocarpon) are among the most economically important and valuable vegetable and fruit crops. They are a major source of biologically active nutritional substances and metabolites which are essential for plant growth, development, stress adaptation and defense. Among these metabolites are the carotenoids which act as accessory pigments for photosynthesis and precursor to plant hormones. Though African eggplants are known to be resistant to various abiotic stresses, the effect of these stresses on secondary metabolites has not been well defined...
January 2017: Food Science & Nutrition
https://www.readbyqxmd.com/read/28067800/multiple-drosophila-tracking-system-with-heading-direction
#17
Pudith Sirigrivatanawong, Shogo Arai, Vladimiros Thoma, Koichi Hashimoto
Machine vision systems have been widely used for image analysis, especially that which is beyond human ability. In biology, studies of behavior help scientists to understand the relationship between sensory stimuli and animal responses. This typically requires the analysis and quantification of animal locomotion. In our work, we focus on the analysis of the locomotion of the fruit fly D r o s o p h i l a m e l a n o g a s t e r , a widely used model organism in biological research. Our system consists of two components: fly detection and tracking...
January 5, 2017: Sensors
https://www.readbyqxmd.com/read/28067293/drug-response-prediction-as-a-link-prediction-problem
#18
Zachary Stanfield, Mustafa Coşkun, Mehmet Koyutürk
Drug response prediction is a well-studied problem in which the molecular profile of a given sample is used to predict the effect of a given drug on that sample. Effective solutions to this problem hold the key for precision medicine. In cancer research, genomic data from cell lines are often utilized as features to develop machine learning models predictive of drug response. Molecular networks provide a functional context for the integration of genomic features, thereby resulting in robust and reproducible predictive models...
January 9, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28066963/phenotiki-an-open-software-and-hardware-platform-for-affordable-and-easy-image-based-phenotyping-of-rosette-shaped-plants
#19
Massimo Minervini, Mario Valerio Giuffrida, Pierdomenico Perata, Sotirios A Tsaftaris
Phenotyping is important to understand plant biology but current solutions are either costly, not versatile or difficult to deploy. To solve this problem, we present Phenotiki, an affordable system for plant phenotyping which, relying on off-the-shelf parts, provides an easy to install and maintain platform, offering an out-of-box experience for a well established phenotyping need: imaging rosette-shaped plants. The accompanying software (with available source code) processes data originating from our device seamlessly and automatically...
January 9, 2017: Plant Journal: for Cell and Molecular Biology
https://www.readbyqxmd.com/read/28065790/comparison-of-cellular-and-transcriptomic-effects-between-electronic-cigarette-vapor-and-cigarette-smoke-in-human-bronchial-epithelial-cells
#20
Sébastien Anthérieu, Anne Garat, Nicolas Beauval, Mélissa Soyez, Delphine Allorge, Guillaume Garçon, Jean-Marc Lo-Guidice
The use of electronic cigarette (e-cig) can be considered as an alternative to smoking. However, due to a lack of thorough toxicological studies, absolute safety of these products cannot be guaranteed. The aim of this in vitro work was to investigate the potential toxicity of e-vapors generated by a smoking machine in human bronchial epithelial BEAS-2B cells cultured at air-liquid interface, in comparison to cigarette smoke (CS). Although CS decreased strongly cell viability from 48min exposure, e-vapors induced no cytotoxicity up to 288min exposure...
January 5, 2017: Toxicology in Vitro: An International Journal Published in Association with BIBRA
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