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https://www.readbyqxmd.com/read/28649444/reverse-engineering-highlights-potential-principles-of-large-gene-regulatory-network-design-and-learning
#1
Clément Carré, André Mas, Gabriel Krouk
Inferring transcriptional gene regulatory networks from transcriptomic datasets is a key challenge of systems biology, with potential impacts ranging from medicine to agronomy. There are several techniques used presently to experimentally assay transcription factors to target relationships, defining important information about real gene regulatory networks connections. These techniques include classical ChIP-seq, yeast one-hybrid, or more recently, DAP-seq or target technologies. These techniques are usually used to validate algorithm predictions...
2017: NPJ Systems Biology and Applications
https://www.readbyqxmd.com/read/28641555/supervised-machine-learning-methods-applied-to-predict-ligand-binding-affinity
#2
Gabriela Sehnem Heck, Val Oliveira Pintro, Richard Rene Pereira, Mauricio Boff de Ávila, Nayara Maria Bernhardt Levin, Walter Filgueira de Azevedo
BACKGROUND: Calculation of ligand-binding affinity is an open problem in computational medicinal chemistry. The ability to computationally predict affinities has a beneficial impact in the early stages of drug development, since it allows a mathematical model to assess protein-ligand interactions. Due to the availability of structural and binding information, machine learning methods have been applied to generate scoring functions with good predictive power. OBJECTIVE: Our goal here is to review recent developments in the application of machine learning methods to predict ligand- binding affinity...
June 22, 2017: Current Medicinal Chemistry
https://www.readbyqxmd.com/read/28628860/in-silico-modeling-on-adme-properties-of-natural-products-classification-models-for-blood-brain-barrier-permeability-its-application-to-traditional-chinese-medicine-and-in-vitro-experimental-validation
#3
Xiuqing Zhang, Ting Liu, Xiaohui Fan, Ni Ai
In silico modeling of blood-brain barrier (BBB) permeability plays an important role in early discovery of central nervous system (CNS) drugs due to its high-throughput and cost-effectiveness. Natural products (NP) have demonstrated considerable therapeutic efficacy against several CNS diseases. However, BBB permeation property of NP is scarcely evaluated both experimentally and computationally. It is well accepted that significant difference in chemical spaces exists between NP and synthetic drugs, which calls into doubt on suitability of available synthetic chemical based BBB permeability models for the evaluation of NP...
June 7, 2017: Journal of Molecular Graphics & Modelling
https://www.readbyqxmd.com/read/28624626/alternative-polyadenylation-patterns-for-novel-gene-discovery-and-classification-in-cancer
#4
Oguzhan Begik, Merve Oyken, Tuna Cinkilli Alican, Tolga Can, Ayse Elif Erson-Bensan
Certain aspects of diagnosis, prognosis, and treatment of cancer patients are still important challenges to be addressed. Therefore, we propose a pipeline to uncover patterns of alternative polyadenylation (APA), a hidden complexity in cancer transcriptomes, to further accelerate efforts to discover novel cancer genes and pathways. Here, we analyzed expression data for 1045 cancer patients and found a significant shift in usage of poly(A) signals in common tumor types (breast, colon, lung, prostate, gastric, and ovarian) compared to normal tissues...
June 15, 2017: Neoplasia: An International Journal for Oncology Research
https://www.readbyqxmd.com/read/28623343/data-driven-nanomechanical-sensing-specific-information-extraction-from-a-complex-system
#5
Kota Shiba, Ryo Tamura, Gaku Imamura, Genki Yoshikawa
Smells are known to be composed of thousands of chemicals with various concentrations, and thus, the extraction of specific information from such a complex system is still challenging. Herein, we report for the first time that the nanomechanical sensing combined with machine learning realizes the specific information extraction, e.g. alcohol content quantification as a proof-of-concept, from the smells of liquors. A newly developed nanomechanical sensor platform, a Membrane-type Surface stress Sensor (MSS), was utilized...
June 16, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28597074/early-metabolic-markers-identify-potential-targets-for-the-prevention-of-type-2-diabetes
#6
Gopal Peddinti, Jeff Cobb, Loic Yengo, Philippe Froguel, Jasmina Kravić, Beverley Balkau, Tiinamaija Tuomi, Tero Aittokallio, Leif Groop
AIMS/HYPOTHESIS: The aims of this study were to evaluate systematically the predictive power of comprehensive metabolomics profiles in predicting the future risk of type 2 diabetes, and to identify a panel of the most predictive metabolic markers. METHODS: We applied an unbiased systems medicine approach to mine metabolite combinations that provide added value in predicting the future incidence of type 2 diabetes beyond known risk factors. We performed mass spectrometry-based targeted, as well as global untargeted, metabolomics, measuring a total of 568 metabolites, in a Finnish cohort of 543 non-diabetic individuals from the Botnia Prospective Study, which included 146 individuals who progressed to type 2 diabetes by the end of a 10 year follow-up period...
June 8, 2017: Diabetologia
https://www.readbyqxmd.com/read/28585183/precision-medicine-for-heart-failure-with-preserved-ejection-fraction-an-overview
#7
Sanjiv J Shah
There are few proven therapies for heart failure with preserved ejection fraction (HFpEF). The lack of therapies, along with increased recognition of the disorder and its underlying pathophysiology, has led to the acknowledgement that HFpEF is heterogeneous and is not likely to respond to a one-size-fits-all approach. Thus, HFpEF is a prime candidate to benefit from a precision medicine approach. For this reason, we have assembled a compendium of papers on the topic of precision medicine in HFpEF in the Journal of Cardiovascular Translational Research...
June 5, 2017: Journal of Cardiovascular Translational Research
https://www.readbyqxmd.com/read/28575077/a-productive-clash-of-perspectives-the-interplay-between-articles-and-authors-perspectives-and-their-impact-on-wikipedia-edits-in-a-controversial-domain
#8
Jens Jirschitzka, Joachim Kimmerle, Iassen Halatchliyski, Julia Hancke, Detmar Meurers, Ulrike Cress
This study examined predictors of the development of Wikipedia articles that deal with controversial issues. We chose a corpus of articles in the German-language version of Wikipedia about alternative medicine as a representative controversial issue. We extracted edits made until March 2013 and categorized them using a supervised machine learning setup as either being pro conventional medicine, pro alternative medicine, or neutral. Based on these categories, we established relevant variables, such as the perspectives of articles and of authors at certain points in time, the (im)balance of an article's perspective, the number of non-neutral edits per article, the number of authors per article, authors' heterogeneity per article, and incongruity between authors' and articles' perspectives...
2017: PloS One
https://www.readbyqxmd.com/read/28562216/support-vector-algorithms-for-optimizing-the-partial-area-under-the-roc-curve
#9
Harikrishna Narasimhan, Shivani Agarwal
The area under the ROC curve (AUC) is a widely used performance measure in machine learning. Increasingly, however, in several applications, ranging from ranking to biometric screening to medicine, performance is measured not in terms of the full area under the ROC curve but in terms of the partial area under the ROC curve between two false-positive rates. In this letter, we develop support vector algorithms for directly optimizing the partial AUC between any two false-positive rates. Our methods are based on minimizing a suitable proxy or surrogate objective for the partial AUC error...
July 2017: Neural Computation
https://www.readbyqxmd.com/read/28556298/predictive-inference-for-best-linear-combination-of-biomarkers-subject-to-limits-of-detection
#10
Tahani Coolen-Maturi
Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning and credit scoring. The receiver operating characteristic (ROC) curve is a useful tool to assess the ability of a diagnostic test to discriminate between two classes or groups. In practice, multiple diagnostic tests or biomarkers are combined to improve diagnostic accuracy. Often, biomarker measurements are undetectable either below or above the so-called limits of detection (LoD). In this paper, nonparametric predictive inference (NPI) for best linear combination of two or more biomarkers subject to limits of detection is presented...
May 28, 2017: Statistics in Medicine
https://www.readbyqxmd.com/read/28545640/artificial-intelligence-in-precision%C3%A2-cardiovascular-medicine
#11
REVIEW
Chayakrit Krittanawong, HongJu Zhang, Zhen Wang, Mehmet Aydar, Takeshi Kitai
Artificial intelligence (AI) is a field of computer science that aims to mimic human thought processes, learning capacity, and knowledge storage. AI techniques have been applied in cardiovascular medicine to explore novel genotypes and phenotypes in existing diseases, improve the quality of patient care, enable cost-effectiveness, and reduce readmission and mortality rates. Over the past decade, several machine-learning techniques have been used for cardiovascular disease diagnosis and prediction. Each problem requires some degree of understanding of the problem, in terms of cardiovascular medicine and statistics, to apply the optimal machine-learning algorithm...
May 30, 2017: Journal of the American College of Cardiology
https://www.readbyqxmd.com/read/28539083/patient-length-of-stay-and-mortality-prediction-a-survey
#12
Aya Awad, Mohamed Bader-El-Den, James McNicholas
Over the past few years, there has been increased interest in data mining and machine learning methods to improve hospital performance, in particular hospitals want to improve their intensive care unit statistics by reducing the number of patients dying inside the intensive care unit. Research has focused on prediction of measurable outcomes, including risk of complications, mortality and length of hospital stay. The length of stay is an important metric both for healthcare providers and patients, influenced by numerous factors...
May 2017: Health Services Management Research
https://www.readbyqxmd.com/read/28538622/towards-precision-medicine-accurate-predictive-modeling-of-infectious-complications-in-combat-casualties
#13
Christopher J Dente, Matthew Bradley, Seth Schobel, Beverly Gaucher, Timothy Buchman, Allan D Kirk, Eric Elster
BACKGROUND: The biomarker profile of trauma patients may allow for the creation of models to assist bedside decision making & prediction of complications. We sought to determine the utility of modeling in the prediction of bacteremia & pneumonia in combat casualties. METHODS: This is a prospective, observational trial of patients with complex wounds treated at Walter Reed National Military Medical Center (2007-2012). Tissue, serum and wound effluent samples were collected during operative interventions until wound closure...
May 22, 2017: Journal of Trauma and Acute Care Surgery
https://www.readbyqxmd.com/read/28524769/machine-learning-for-epigenetics-and-future-medical-applications
#14
Lawrence B Holder, M Muksitul Haque, Michael K Skinner
Understanding epigenetic processes holds immense promise for medical applications. Advances in Machine Learning (ML) are critical to realize this promise. Previous studies used epigenetic data sets associated with the germline transmission of epigenetic transgenerational inheritance of disease and novel ML approaches to predict genome-wide locations of critical epimutations. A combination of Active Learning (ACL) and Imbalanced Class Learning (ICL) was used to address past problems with ML to develop a more efficient feature selection process and address the imbalance problem in all genomic data sets...
May 19, 2017: Epigenetics: Official Journal of the DNA Methylation Society
https://www.readbyqxmd.com/read/28507231/biological-modelling-of-a-computational-spiking-neural-network-with-neuronal-avalanches
#15
Xiumin Li, Qing Chen, Fangzheng Xue
In recent years, an increasing number of studies have demonstrated that networks in the brain can self-organize into a critical state where dynamics exhibit a mixture of ordered and disordered patterns. This critical branching phenomenon is termed neuronal avalanches. It has been hypothesized that the homeostatic level balanced between stability and plasticity of this critical state may be the optimal state for performing diverse neural computational tasks. However, the critical region for high performance is narrow and sensitive for spiking neural networks (SNNs)...
June 28, 2017: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
https://www.readbyqxmd.com/read/28503676/learning-optimal-individualized-treatment-rules-from-electronic-health-record-data
#16
Yuanjia Wang, Peng Wu, Ying Liu, Chunhua Weng, Donglin Zeng
Medical research is experiencing a paradigm shift from "one-size-fits-all" strategy to a precision medicine approach where the right therapy, for the right patient, and at the right time, will be prescribed. We propose a statistical method to estimate the optimal individualized treatment rules (ITRs) that are tailored according to subject-specific features using electronic health records (EHR) data. Our approach merges statistical modeling and medical domain knowledge with machine learning algorithms to assist personalized medical decision making using EHR...
October 2016: IEEE International Conference on Healthcare Informatics IEEE International Conference on Healthcare Informatics
https://www.readbyqxmd.com/read/28503375/network-science-meets-respiratory-medicine-for-osas-phenotyping-and-severity-prediction
#17
Stefan Mihaicuta, Mihai Udrescu, Alexandru Topirceanu, Lucretia Udrescu
Obstructive sleep apnea syndrome (OSAS) is a common clinical condition. The way that OSAS risk factors associate and converge is not a random process. As such, defining OSAS phenotypes fosters personalized patient management and population screening. In this paper, we present a network-based observational, retrospective study on a cohort of 1,371 consecutive OSAS patients and 611 non-OSAS control patients in order to explore the risk factor associations and their correlation with OSAS comorbidities. To this end, we construct the Apnea Patients Network (APN) using patient compatibility relationships according to six objective parameters: age, gender, body mass index (BMI), blood pressure (BP), neck circumference (NC) and the Epworth sleepiness score (ESS)...
2017: PeerJ
https://www.readbyqxmd.com/read/28490744/precision-radiology-predicting-longevity-using-feature-engineering-and-deep-learning-methods-in-a-radiomics-framework
#18
Luke Oakden-Rayner, Gustavo Carneiro, Taryn Bessen, Jacinto C Nascimento, Andrew P Bradley, Lyle J Palmer
Precision medicine approaches rely on obtaining precise knowledge of the true state of health of an individual patient, which results from a combination of their genetic risks and environmental exposures. This approach is currently limited by the lack of effective and efficient non-invasive medical tests to define the full range of phenotypic variation associated with individual health. Such knowledge is critical for improved early intervention, for better treatment decisions, and for ameliorating the steadily worsening epidemic of chronic disease...
May 10, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28455973/markers-of-arterial-health-could-serve-as-accurate-non-invasive-predictors-of-human-biological-and-chronological-age
#19
Alexander Fedintsev, Daria Kashtanova, Olga Tkacheva, Irina Strazhesko, Anna Kudryavtseva, Ancha Baranova, Alexey Moskalev
The decline in functional capacity is unavoidable consequence of the process of aging. While many anti-aging interventions have been proposed, clinical investigations into anti-aging medicine are limited by lack of reliable techniques for evaluating the rate of ageing. Here we present simple, accurate and cost-efficient techniques for estimation of human biological age, Male and Female Arterial Indices. We started with developing a model which accurately predicts chronological age. Using machine learning, we arrived on a set of four predictors, all of which reflect the functioning of the cardiovascular system...
April 2017: Aging
https://www.readbyqxmd.com/read/28439010/cyclops-reveals-human-transcriptional-rhythms-in-health-and-disease
#20
Ron C Anafi, Lauren J Francey, John B Hogenesch, Junhyong Kim
Circadian rhythms modulate many aspects of physiology. Knowledge of the molecular basis of these rhythms has exploded in the last 20 years. However, most of these data are from model organisms, and translation to clinical practice has been limited. Here, we present an approach to identify molecular rhythms in humans from thousands of unordered expression measurements. Our algorithm, cyclic ordering by periodic structure (CYCLOPS), uses evolutionary conservation and machine learning to identify elliptical structure in high-dimensional data...
May 16, 2017: Proceedings of the National Academy of Sciences of the United States of America
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