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https://www.readbyqxmd.com/read/28346487/ml2motif-reliable-extraction-of-discriminative-sequence-motifs-from-learning-machines
#1
Marina M-C Vidovic, Marius Kloft, Klaus-Robert Müller, Nico Görnitz
High prediction accuracies are not the only objective to consider when solving problems using machine learning. Instead, particular scientific applications require some explanation of the learned prediction function. For computational biology, positional oligomer importance matrices (POIMs) have been successfully applied to explain the decision of support vector machines (SVMs) using weighted-degree (WD) kernels. To extract relevant biological motifs from POIMs, the motifPOIM method has been devised and showed promising results on real-world data...
2017: PloS One
https://www.readbyqxmd.com/read/28345042/human-genetic-and-metabolite-variation-reveals-that-methylthioadenosine-is-a-prognostic-biomarker-and-an-inflammatory-regulator-in-sepsis
#2
Liuyang Wang, Emily R Ko, James J Gilchrist, Kelly J Pittman, Anna Rautanen, Matti Pirinen, J Will Thompson, Laura G Dubois, Raymond J Langley, Sarah L Jaslow, Raul E Salinas, D Clayburn Rouse, M Arthur Moseley, Salim Mwarumba, Patricia Njuguna, Neema Mturi, Thomas N Williams, J Anthony G Scott, Adrian V S Hill, Christopher W Woods, Geoffrey S Ginsburg, Ephraim L Tsalik, Dennis C Ko
Sepsis is a deleterious inflammatory response to infection with high mortality. Reliable sepsis biomarkers could improve diagnosis, prognosis, and treatment. Integration of human genetics, patient metabolite and cytokine measurements, and testing in a mouse model demonstrate that the methionine salvage pathway is a regulator of sepsis that can accurately predict prognosis in patients. Pathway-based genome-wide association analysis of nontyphoidal Salmonella bacteremia showed a strong enrichment for single-nucleotide polymorphisms near the components of the methionine salvage pathway...
March 2017: Science Advances
https://www.readbyqxmd.com/read/28344634/an-image-analysis-pipeline-for-automated-classification-of-imaging-light-conditions-and-for-quantification-of-wheat-canopy-cover-time-series-in-field-phenotyping
#3
Kang Yu, Norbert Kirchgessner, Christoph Grieder, Achim Walter, Andreas Hund
BACKGROUND: Robust segmentation of canopy cover (CC) from large amounts of images taken under different illumination/light conditions in the field is essential for high throughput field phenotyping (HTFP). We attempted to address this challenge by evaluating different vegetation indices and segmentation methods for analyzing images taken at varying illuminations throughout the early growth phase of wheat in the field. 40,000 images taken on 350 wheat genotypes in two consecutive years were assessed for this purpose...
2017: Plant Methods
https://www.readbyqxmd.com/read/28344110/toward-a-systematic-exploration-of-nano-bio-interactions
#4
REVIEW
Xue Bai, Fang Liu, Yin Liu, Cong Li, Shenqing Wang, Hongyu Zhou, Wenyi Wang, Hao Zhu, Dave Winkler, Bing Yan
Many studies of nanomaterials make non-systematic alterations of nanoparticle physicochemical properties. Given the immense size of the property space for nanomaterials, such approaches are not very useful in elucidating fundamental relationships between inherent physicochemical properties of these materials and their interactions with, and effects on, biological systems. Data driven artificial intelligence methods such as machine learning algorithms have proven highly effective in generating models with good predictivity and some degree of interpretability...
March 24, 2017: Toxicology and Applied Pharmacology
https://www.readbyqxmd.com/read/28343766/prediction-of-high-on-treatment-platelet-reactivity-in-clopidogrel-treated-patients-with-acute-coronary-syndromes
#5
G M Podda, E Grossi, T Palmerini, M Buscema, E A Femia, D Della Riva, S de Servi, P Calabrò, F Piscione, D Maffeo, A Toso, C Palmieri, M De Carlo, D Capodanno, P Genereux, M Cattaneo
BACKGROUND: About 40% of clopidogrel-treated patients display high platelet reactivity (HPR). Alternative treatments of HPR patients, identified by platelet function tests, failed to improve their clinical outcomes in large randomized clinical trials. A more appealing alternative would be to identify HPR patients a priori, based on the presence/absence of demographic, clinical and genetic factors that affect PR. Due to the complexity and multiplicity of these factors, traditional statistical methods (TSMs) fail to identify a priori HPR patients accurately...
March 18, 2017: International Journal of Cardiology
https://www.readbyqxmd.com/read/28342697/recent-publications-from-the-alzheimer-s-disease-neuroimaging-initiative-reviewing-progress-toward-improved-ad-clinical-trials
#6
REVIEW
Michael W Weiner, Dallas P Veitch, Paul S Aisen, Laurel A Beckett, Nigel J Cairns, Robert C Green, Danielle Harvey, Clifford R Jack, William Jagust, John C Morris, Ronald C Petersen, Andrew J Saykin, Leslie M Shaw, Arthur W Toga, John Q Trojanowski
INTRODUCTION: The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the 450+ publications using ADNI data during 2014 and 2015. METHODS: We used standard searches to find publications using ADNI data. RESULTS: (1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses...
March 22, 2017: Alzheimer's & Dementia: the Journal of the Alzheimer's Association
https://www.readbyqxmd.com/read/28342339/a-novel-hybrid-strategy-for-pm2-5-concentration-analysis-and-prediction
#7
Ping Jiang, Qingli Dong, Peizhi Li
The analysis and prediction of air pollutants are of great significance in environmental research today since airborne pollution is a substantial threat, especially in urban agglomerations of China. To develop more effective warning systems and management advice, the authorities and city dwellers need more accurate forecasts of the air pollution. Most previous analysis systems were based on costly observation apparatus at fixed sites, forecasting models were usually built on observations within a certain range, and some observations contained biases...
March 22, 2017: Journal of Environmental Management
https://www.readbyqxmd.com/read/28341746/leveraging-sequence-based-faecal-microbial-community-survey-data-to-identify-a-composite-biomarker-for-colorectal-cancer
#8
Manasi S Shah, Todd Z DeSantis, Thomas Weinmaier, Paul J McMurdie, Julia L Cope, Adam Altrichter, Jose-Miguel Yamal, Emily B Hollister
OBJECTIVE: Colorectal cancer (CRC) is the second leading cause of cancer-associated mortality in the USA. The faecal microbiome may provide non-invasive biomarkers of CRC and indicate transition in the adenoma-carcinoma sequence. Re-analysing raw sequence and metadata from several studies uniformly, we sought to identify a composite and generalisable microbial marker for CRC. DESIGN: Raw 16S rRNA gene sequence data sets from nine studies were processed with two pipelines, (1) QIIME closed reference (QIIME-CR) or (2) a strain-specific method herein termed SS-UP (Strain Select, UPARSE bioinformatics pipeline)...
March 24, 2017: Gut
https://www.readbyqxmd.com/read/28340955/a-practical-framework-toward-prediction-of-breaking-force-and-disintegration-of-tablet-formulations-using-machine-learning-tools
#9
Ilgaz Akseli, Jingjin Xie, Leon Schultz, Nadia Ladyzhynsky, Tommasina Bramante, Xiaorong He, Rich Deanne, Keith R Horspool, Robert Schwabe
Enabling the paradigm of quality by design requires the ability to quantitatively correlate material properties and process variables to measureable product performance attributes. Conventional, quality-by-test methods for determining tablet breaking force and disintegration time usually involve destructive tests, which consume significant amount of time and labor and provide limited information. Recent advances in material characterization, statistical analysis, and machine learning have provided multiple tools that have the potential to develop nondestructive, fast, and accurate approaches in drug product development...
January 2017: Journal of Pharmaceutical Sciences
https://www.readbyqxmd.com/read/28339690/automated-classification-of-eligibility-criteria-in-clinical-trials-to-facilitate-patient-trial-matching-for-specific-patient-populations
#10
Kevin Zhang, Dina Demner-Fushman
Objective: To develop automated classification methods for eligibility criteria in ClinicalTrials.gov to facilitate patient-trial matching for specific populations such as persons living with HIV or pregnant women. Materials and Methods: We annotated 891 interventional cancer trials from ClinicalTrials.gov based on their eligibility for human immunodeficiency virus (HIV)-positive patients using their eligibility criteria. These annotations were used to develop classifiers based on regular expressions and machine learning (ML)...
February 19, 2017: Journal of the American Medical Informatics Association: JAMIA
https://www.readbyqxmd.com/read/28338845/computational-psychiatry-and-the-challenge-of-schizophrenia
#11
John H Krystal, John D Murray, Adam M Chekroud, Philip R Corlett, Genevieve Yang, Xiao-Jing Wang, Alan Anticevic
Schizophrenia research is plagued by enormous challenges in integrating and analyzing large datasets and difficulties developing formal theories related to the etiology, pathophysiology, and treatment of this disorder. Computational psychiatry provides a path to enhance analyses of these large and complex datasets and to promote the development and refinement of formal models for features of this disorder. This presentation introduces the reader to the notion of computational psychiatry and describes discovery-oriented and theory-driven applications to schizophrenia involving machine learning, reinforcement learning theory, and biophysically-informed neural circuit models...
March 8, 2017: Schizophrenia Bulletin
https://www.readbyqxmd.com/read/28338573/a-machine-learning-based-surface-electromyography-topography-evaluation-for-prognostic-prediction-of-functional-restoration-rehabilitation-in-chronic-low-back-pain
#12
Naifu Jiang, Keith Dip-Kei Luk, Yong Hu
STUDY DESIGN: A retrospective study. OBJECTIVE: To investigate the feasibility and applicability of support vector machine (SVM) algorithm in classifying patients with LBP who would obtain satisfactory or unsatisfactory progress after the functional restoration rehabilitation program. SUMMARY OF BACKGROUND DATA: Dynamic surface electromyography (SEMG) topography has demonstrated the potential use in predicting the prognosis of functional restoration rehabilitation for patients with low back pain (LBP)...
March 23, 2017: Spine
https://www.readbyqxmd.com/read/28337565/blood-trace-metals-in-a-sporadic-amyotrophic-lateral-sclerosis-geographical-cluster
#13
Stefano De Benedetti, Giorgio Lucchini, Cristian Del Bò, Valeria Deon, Alessandro Marocchi, Silvana Penco, Christian Lunetta, Elisabetta Gianazza, Francesco Bonomi, Stefania Iametti
Amyotrophic lateral sclerosis (ALS) is a fatal disorder with unknown etiology, in which genetic and environmental factors interplay to determine the onset and the course of the disease. Exposure to toxic metals has been proposed to be involved in the etiology of the disease either through a direct damage or by promoting oxidative stress. In this study we evaluated the concentration of a panel of metals in serum and whole blood of a small group of sporadic patients, all living in a defined geographical area, for which acid mine drainage has been reported...
March 23, 2017: Biometals: An International Journal on the Role of Metal Ions in Biology, Biochemistry, and Medicine
https://www.readbyqxmd.com/read/28336805/what-is-data-ethics
#14
Luciano Floridi, Mariarosaria Taddeo
This theme issue has the founding ambition of landscaping data ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithms (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values)...
December 28, 2016: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
https://www.readbyqxmd.com/read/28335739/identification-of-long-non-coding-transcripts-with-feature-selection-a-comparative-study
#15
Giovanna M M Ventola, Teresa M R Noviello, Salvatore D'Aniello, Antonietta Spagnuolo, Michele Ceccarelli, Luigi Cerulo
BACKGROUND: The unveiling of long non-coding RNAs as important gene regulators in many biological contexts has increased the demand for efficient and robust computational methods to identify novel long non-coding RNAs from transcripts assembled with high throughput RNA-seq data. Several classes of sequence-based features have been proposed to distinguish between coding and non-coding transcripts. Among them, open reading frame, conservation scores, nucleotide arrangements, and RNA secondary structure have been used with success in literature to recognize intergenic long non-coding RNAs, a particular subclass of non-coding RNAs...
March 23, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28335394/motor-function-evaluation-of-hemiplegic-upper-extremities-using-data-fusion-from-wearable-inertial-and-surface-emg-sensors
#16
Yanran Li, Xu Zhang, Yanan Gong, Ying Cheng, Xiaoping Gao, Xiang Chen
Quantitative evaluation of motor function is of great demand for monitoring clinical outcome of applied interventions and further guiding the establishment of therapeutic protocol. This study proposes a novel framework for evaluating upper limb motor function based on data fusion from inertial measurement units (IMUs) and surface electromyography (EMG) sensors. With wearable sensors worn on the tested upper limbs, subjects were asked to perform eleven straightforward, specifically designed canonical upper-limb functional tasks...
March 13, 2017: Sensors
https://www.readbyqxmd.com/read/28333956/discriminating-between-hur-and-ttp-binding-sites-using-the-k-spectrum-kernel-method
#17
Shweta Bhandare, Debra S Goldberg, Robin Dowell
BACKGROUND: The RNA binding proteins (RBPs) human antigen R (HuR) and Tristetraprolin (TTP) are known to exhibit competitive binding but have opposing effects on the bound messenger RNA (mRNA). How cells discriminate between the two proteins is an interesting problem. Machine learning approaches, such as support vector machines (SVMs), may be useful in the identification of discriminative features. However, this method has yet to be applied to studies of RNA binding protein motifs. RESULTS: Applying the k-spectrum kernel to a support vector machine (SVM), we first verified the published binding sites of both HuR and TTP...
2017: PloS One
https://www.readbyqxmd.com/read/28333644/random-forest-classifier-for-zero-shot-learning-based-on-relative-attribute
#18
Yuhu Cheng, Xue Qiao, Xuesong Wang, Qiang Yu
For the zero-shot image classification with relative attributes (RAs), the traditional method requires that not only all seen and unseen images obey Gaussian distribution, but also the classifications on testing samples are made by maximum likelihood estimation. We therefore propose a novel zero-shot image classifier called random forest based on relative attribute. First, based on the ordered and unordered pairs of images from the seen classes, the idea of ranking support vector machine is used to learn ranking functions for attributes...
March 21, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28333585/fast-estimation-of-approximate-matrix-ranks-using-spectral-densities
#19
Shashanka Ubaru, Yousef Saad, Abd-Krim Seghouane
Many machine learning and data-related applications require the knowledge of approximate ranks of large data matrices at hand. This letter presents two computationally inexpensive techniques to estimate the approximate ranks of such matrices. These techniques exploit approximate spectral densities, popular in physics, which are probability density distributions that measure the likelihood of finding eigenvalues of the matrix at a given point on the real line. Integrating the spectral density over an interval gives the eigenvalue count of the matrix in that interval...
March 23, 2017: Neural Computation
https://www.readbyqxmd.com/read/28333183/machine-learning-algorithms-for-objective-remission-and-clinical-outcomes-with-thiopurines
#20
Akbar K Waljee, Kay Sauder, Anand Patel, Sandeep Segar, Boang Liu, Yiwei Zhang, Ji Zhu, Ryan W Stidham, Ulysses Balis, Peter D R Higgins
Background and Aims: Big data analytics leverage patterns in data to harvest valuable information, but are rarely implemented in clinical care. Optimising thiopurine therapy for inflammatory bowel disease [IBD] has proved difficult. Current methods using 6-thioguanine nucleotide [6-TGN] metabolites have failed in randomized controlled trials [RCTs], and have not been used to predict objective remission [OR]. Our aims were to: 1) develop machine learning algorithms [MLA] using laboratory values and age to identify patients in objective remission on thiopurines; and 2) determine whether achieving algorithm-predicted objective remission resulted in fewer clinical events per year...
March 14, 2017: Journal of Crohn's & Colitis
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