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https://www.readbyqxmd.com/read/28743071/prediction-of-protein-structural-class-for-low-similarity-sequences-using-chou-s-pseudo-amino-acid-composition-and-wavelet-denoising
#1
Bin Yu, Lifeng Lou, Shan Li, Yusen Zhang, Wenying Qiu, Xue Wu, Minghui Wang, Baoguang Tian
Prediction of protein structural class plays an important role in protein structure and function analysis, drug design and many other biological applications. Prediction of protein structural class for low-similarity sequences is still a challenging task. Based on the theory of wavelet denoising, this paper presents a novel method of prediction of protein structural class for the first time. Firstly, the features of the protein sequence are extracted by using Chou's pseudo amino acid composition (PseAAC). Then the extracted feature information is denoised by two-dimensional (2D) wavelet...
July 14, 2017: Journal of Molecular Graphics & Modelling
https://www.readbyqxmd.com/read/28743031/high-ph-thresholding-of-beef-with-vnir-hyperspectral-imaging
#2
Stuart O J Crichton, Sascha M Kirchner, Victoria Porley, Stefanie Retz, Gardis von Gersdorff, Oliver Hensel, Barbara Sturm
Initial quality grading of meat is generally carried out using invasive and occasionally destructive sampling for the purposes of pH testing. Precise pH and thresholds exist to allow the classification of different statuses of meat, e.g. for detection of dry, firm, and dark (DFD) (when dealing with cattle and sheep), or pale, soft exudative meat (when dealing with pork). This paper illustrates that threshold detection for pH level in beef with different freshness levels (fresh, fresh frozen-thawed, matured, and matured frozen-thawed)...
July 18, 2017: Meat Science
https://www.readbyqxmd.com/read/28740541/a-selective-ensemble-classification-method-combining-mammography-images-with-ultrasound-images-for-breast-cancer-diagnosis
#3
Jinyu Cong, Benzheng Wei, Yunlong He, Yilong Yin, Yuanjie Zheng
Breast cancer has been one of the main diseases that threatens women's life. Early detection and diagnosis of breast cancer play an important role in reducing mortality of breast cancer. In this paper, we propose a selective ensemble method integrated with the KNN, SVM, and Naive Bayes to diagnose the breast cancer combining ultrasound images with mammography images. Our experimental results have shown that the selective classification method with an accuracy of 88.73% and sensitivity of 97.06% is efficient for breast cancer diagnosis...
2017: Computational and Mathematical Methods in Medicine
https://www.readbyqxmd.com/read/28738563/urinary-volatile-fingerprint-based-on-mass-spectrometry-for-the-discrimination-of-patients-with-lung-cancer-and-controls
#4
Álvaro García Ramos, Ana Pérez Antón, Miguel Del Nogal Sánchez, José Luis Pérez Pavón, Bernardo Moreno Cordero
Profile signals of urine samples corresponding to patients with lung cancer and controls were obtained using a non-separative methodology. The method is based on the coupling of a headspace sampler, a programed temperature vaporizer and a mass spectrometer (HS-PTV-MS). With only a centrifugation step as prior sample treatment, the samples were subjected to the headspace generation process and the volatiles generated were introduced into the PTV where they were trapped in the Tenax® packed liner while the solvent was purged...
November 1, 2017: Talanta
https://www.readbyqxmd.com/read/28737713/quality-assessment-of-gentiana-rigescens-from-different-geographical-origins-using-ft-ir-spectroscopy-combined-with-hplc
#5
Zhe Wu, Yanli Zhao, Ji Zhang, Yuanzhong Wang
Gentiana rigescens is a precious herbal medicine in China because of its liver-protective and choleretic effects. A method for the qualitative identification and quantitative evaluation of G. rigescens from Yunnan Province, China, has been developed employing Fourier transform infrared (FT-IR) spectroscopy and high performance liquid chromatography (HPLC) with the aid of chemometrics such as partial least squares discriminant analysis (PLS-DA) and support vector machines (SVM) regression. Our results indicated that PLS-DA model could efficiently discriminate G...
July 24, 2017: Molecules: a Journal of Synthetic Chemistry and Natural Product Chemistry
https://www.readbyqxmd.com/read/28737705/emotion-recognition-from-chinese-speech-for-smart-affective-services-using-a-combination-of-svm-and-dbn
#6
Lianzhang Zhu, Leiming Chen, Dehai Zhao, Jiehan Zhou, Weishan Zhang
Accurate emotion recognition from speech is important for applications like smart health care, smart entertainment, and other smart services. High accuracy emotion recognition from Chinese speech is challenging due to the complexities of the Chinese language. In this paper, we explore how to improve the accuracy of speech emotion recognition, including speech signal feature extraction and emotion classification methods. Five types of features are extracted from a speech sample: mel frequency cepstrum coefficient (MFCC), pitch, formant, short-term zero-crossing rate and short-term energy...
July 24, 2017: Sensors
https://www.readbyqxmd.com/read/28737702/a-novel-and-practical-chromatographic-fingerprint-roc-svm-strategy-applied-to-quality-analysis-of-traditional-chinese-medicine-injections-using-kudiezi-injection-as-a-case-study
#7
Bin Yang, Yuan Wang, Lanlan Shan, Jingtao Zou, Yuanyuan Wu, Feifan Yang, Yani Zhang, Yubo Li, Yanjun Zhang
Fingerprinting is widely and commonly used in the quality control of traditional Chinese medicine (TCM) injections. However, current studies informed that the fingerprint similarity evaluation was less sensitive and easily generated false positive results. For this reason, a novel and practical chromatographic "Fingerprint-ROC-SVM" strategy was established by using KuDieZi (KDZ) injection as a case study in the present article. Firstly, the chromatographic fingerprints of KDZ injection were obtained by UPLC and the common characteristic peaks were identified with UPLC/Q-TOF-MS under the same chromatographic conditions...
July 23, 2017: Molecules: a Journal of Synthetic Chemistry and Natural Product Chemistry
https://www.readbyqxmd.com/read/28737267/appearance-and-characterization-of-fruit-image-textures-for-quality-sorting-using-wavelet-transform-and-genetic-algorithms
#8
Suchitra Khoje
Images of four qualities of Mangoes and Guavas are evaluated for colour and textural features to characterize and classify them, and to model the fruit appearance grading. The paper discusses three approaches to identify most discriminating texture features of both the fruits. In the first approach, fruit's colour and texture features are selected using Mahalanobis distance. A total of 20 colour features and 40 textural features are extracted for analysis. Using Mahalanobis distance and feature inter-correlation analyses, one best colour features [mean of a* (L*a*b* colour space) and two textural features [energy a*, contrast of H*]are selected as features for guava while two best colour features [R std, H std] and one textural features [energy b*]are selected as features for Mangoes with the highest discriminate power...
July 24, 2017: Journal of Texture Studies
https://www.readbyqxmd.com/read/28734799/eeg-analysis-of-seizure-patterns-using-visibility-graphs-for-detection-of-generalized-seizures
#9
Lei Wang, Xi Long, Johan B A M Arends, Ronald M Aarts
BACKGROUND: The traditional EEG features in the time and frequency domain show limited seizure detection performance in the epileptic population with intellectual disability (ID). In addition, the influence of EEG seizure patterns on detection performance was less studied. NEW METHOD: A single-channel EEG signal can be mapped into visibility graphs (VGS), including basic visibility graph (VG), horizontal VG (HVG), and difference VG (DVG). These graphs were used to characterize different EEG seizure patterns...
July 19, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/28734525/classification-of-cardiovascular-tissues-using-lbp-based-descriptors-and-a-cascade-svm
#10
Claudia Mazo, Enrique Alegre, Maria Trujillo
BACKGROUND AND OBJECTIVE: Histological images have characteristics, such as texture, shape, colour and spatial structure, that permit the differentiation of each fundamental tissue and organ. Texture is one of the most discriminative features. The automatic classification of tissues and organs based on histology images is an open problem, due to the lack of automatic solutions when treating tissues without pathologies. METHOD: In this paper, we demonstrate that it is possible to automatically classify cardiovascular tissues using texture information and Support Vector Machines (SVM)...
August 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28734365/automatic-feed-phase-identification-in-multivariate-bioprocess-profiles-by-sequential-binary-classification
#11
Ramin Nikzad-Langerodi, Edwin Lughofer, Susanne Saminger-Platz, Thomas Zahel, Patrick Sagmeister, Christoph Herwig
In this paper, we propose a new strategy for retrospective identification of feed phases from online sensor-data enriched feed profiles of an Escherichia Coli (E. coli) fed-batch fermentation process. In contrast to conventional (static), data-driven multi-class machine learning (ML), we exploit process knowledge in order to constrain our classification system yielding more parsimonious models compared to static ML approaches. In particular, we enforce unidirectionality on a set of binary, multivariate classifiers trained to discriminate between adjacent feed phases by linking the classifiers through a one-way switch...
August 22, 2017: Analytica Chimica Acta
https://www.readbyqxmd.com/read/28732980/synthesis-of-amine-modified-zeolitic-imidazolate-framework-8-ultrasound-assisted-dye-removal-and-modeling
#12
Jafar Abdi, Manouchehr Vossoughi, Niyaz Mohammad Mahmoodi, Iran Alemzadeh
The present research is focused on the ultrasound assisted adsorption of Acid blue 92 (AB92) and Direct red 80 (DR80) as anionic dyes in single and binary systems onto zeolitic imidazolate framework (ZIF-8) functionalized with 3-Aminopropyltrimethoxysilane (APTES). Different techniques such as Fourier transform infrared (FTIR), scanning electron microscope (SEM), field emission scanning electron microscopy (FE-SEM), X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET) and thermogravimetric analyses (TGA) were used to characterize the prepared adsorbent...
November 2017: Ultrasonics Sonochemistry
https://www.readbyqxmd.com/read/28732281/epileptic-seizure-detection-in-eegs-signals-based-on-the-weighted-visibility-graph-entropy
#13
Zeynab Mohammadpoory, Mahda Nasrolahzadeh, Javad Haddadnia
PURPOSE: Epileptic seizure detection has been a complex task for both researchers and specialist in that the assessment of epilepsy is difficult because, electroencephalogram (EEG) signals are chaotic and non-stationary. METHOD: This paper proposes a new method based on weighted visibility graph entropy (WVGE) to identify seizure from EEG signals. Single channel EEG signals are mapped onto the WVGs and WVGEs are calculated from these WVGs. Then some features are extracted of WVGEs and given to classifiers to investigate the performance of these features to classify the brain signals into three groups of normal (healthy), seizure free (interictal) and during a seizure (ictal) groups...
July 11, 2017: Seizure: the Journal of the British Epilepsy Association
https://www.readbyqxmd.com/read/28729956/predicting-the-host-of-influenza-viruses-based-on-the-word-vector
#14
Beibei Xu, Zhiying Tan, Kenli Li, Taijiao Jiang, Yousong Peng
Newly emerging influenza viruses continue to threaten public health. A rapid determination of the host range of newly discovered influenza viruses would assist in early assessment of their risk. Here, we attempted to predict the host of influenza viruses using the Support Vector Machine (SVM) classifier based on the word vector, a new representation and feature extraction method for biological sequences. The results show that the length of the word within the word vector, the sequence type (DNA or protein) and the species from which the sequences were derived for generating the word vector all influence the performance of models in predicting the host of influenza viruses...
2017: PeerJ
https://www.readbyqxmd.com/read/28729763/serum-and-plasma-metabolomic-biomarkers-for-lung-cancer
#15
Nishith Kumar, Md Shahjaman, Md Nurul Haque Mollah, S M Shahinul Islam, Md Aminul Hoque
In drug invention and early disease prediction of lung cancer, metabolomic biomarker detection is very important. Mortality rate can be decreased, if cancer is predicted at the earlier stage. Recent diagnostic techniques for lung cancer are not prognosis diagnostic techniques. However, if we know the name of the metabolites, whose intensity levels are considerably changing between cancer subject and control subject, then it will be easy to early diagnosis the disease as well as to discover the drug. Therefore, in this paper we have identified the influential plasma and serum blood sample metabolites for lung cancer and also identified the biomarkers that will be helpful for early disease prediction as well as for drug invention...
2017: Bioinformation
https://www.readbyqxmd.com/read/28728059/iterative-variational-mode-decomposition-based-automated-detection-of-glaucoma-using-fundus-images
#16
Shishir Maheshwari, Ram Bilas Pachori, Vivek Kanhangad, Sulatha V Bhandary, U Rajendra Acharya
Glaucoma is one of the leading causes of permanent vision loss. It is an ocular disorder caused by increased fluid pressure within the eye. The clinical methods available for the diagnosis of glaucoma require skilled supervision. They are manual, time consuming, and out of reach of common people. Hence, there is a need for an automated glaucoma diagnosis system for mass screening. In this paper, we present a novel method for an automated diagnosis of glaucoma using digital fundus images. Variational mode decomposition (VMD) method is used in an iterative manner for image decomposition...
June 19, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28727421/shallow-representation-learning-via-kernel-pca-improves-qsar-modelability
#17
Stefano E Rensi, Russ B Altman
Linear models offer a robust, flexible, and computationally efficient set of tools for modeling quantitative structure activity relationships (QSAR), but have been eclipsed in performance by non-linear methods. Support vector machines (SVMs) and neural networks are currently among the most popular and accurate QSAR methods because they learn new representations of the data that greatly improve modelability. In this work we use shallow representation learning to improve the accuracy of L1 regularized logistic regression (LASSO) and meet the performance of Tanimoto SVM...
July 20, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28725174/altered-functional-connectivity-following-an-inflammatory-white-matter-injury-in-the-newborn-rat-a-high-spatial-and-temporal-resolution-intrinsic-optical-imaging-study
#18
Edgar Guevara, Wyston C Pierre, Camille Tessier, Luis Akakpo, Irène Londono, Frédéric Lesage, Gregory A Lodygensky
Very preterm newborns have an increased risk of developing an inflammatory cerebral white matter injury that may lead to severe neuro-cognitive impairment. In this study we performed functional connectivity (fc) analysis using resting-state optical imaging of intrinsic signals (rs-OIS) to assess the impact of inflammation on resting-state networks (RSN) in a pre-clinical model of perinatal inflammatory brain injury. Lipopolysaccharide (LPS) or saline injections were administered in postnatal day (P3) rat pups and optical imaging of intrinsic signals were obtained 3 weeks later...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28722418/urine-metabonomics-reveals-early-biomarkers-in-diabetic-cognitive-dysfunction
#19
Lili Song, Pengwei Zhuang, Mengya Lin, Mingqin Kang, Hongyue Liu, Yuping Zhang, Zhen Yang, Yunlong Chen, Yanjun Zhang
Recently, increasing attention has been paid to diabetic encephalopathy which is one of frequent diabetic complications and affects nearly 30% diabetics. Since cognitive dysfunction from diabetic encephalopathy might develop irreversible dementia, early diagnosis and detection of this disease is of great significance for its prevention and treatment. This study is to investigate the early specific metabolites biomarkers in the urine prior to the onset of diabetic cognitive dysfunction (DCD) by using metabolomics technology...
July 19, 2017: Journal of Proteome Research
https://www.readbyqxmd.com/read/28720710/application-of-response-surface-methods-to-determine-conditions-for-optimal-genomic-prediction
#20
Réka Howard, Alicia L Carriquiry, William D Beavis
An epistatic genetic architecture can have a significant impact on prediction accuracies of genomic prediction (GP) methods. Machine learning methods predict traits composed of epistatic genetic architectures more accurately than statistical methods based on additive mixed linear models. The differences between these types of GP methods suggest a diagnostic for revealing genetic architectures underlying traits of interest. In addition to genetic architecture, the performance of GP methods may be influenced by the sample size of the training population, the number of QTL, and the proportion of phenotypic variability due to genotypic variability (heritability)...
July 18, 2017: G3: Genes—Genomes—Genetics
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