keyword
MENU ▼
Read by QxMD icon Read
search

Lasso

keyword
https://www.readbyqxmd.com/read/27913395/metabolomic-characterization-of-hepatocellular-carcinoma-in-patients-with-liver-cirrhosis-for-biomarker-discovery
#1
Cristina Di Poto, Alessia Ferrarini, Yi Zhao, Rency S Varghese, Chao Tu, Yiming Zuo, Minkun Wang, Mohammad R Nezami Ranjbar, Yue Luo, Chi Zhang, Chirag S Desai, Kirti Shetty, Mahlet G Tadesse, Habtom W Ressom
BACKGROUND: Metabolomics plays an important role in providing insight into the etiology and mechanisms of hepatocellular carcinoma (HCC). This is accomplished by a comprehensive analysis of patterns involved in metabolic alterations in human specimens. This study compares the levels of plasma metabolites in HCC cases versus cirrhotic patients and evaluates the ability of candidate metabolites in distinguishing the two groups. Also, it investigates the combined use of metabolites and clinical covariates for detection of HCC in patients with liver cirrhosis...
December 2, 2016: Cancer Epidemiology, Biomarkers & Prevention
https://www.readbyqxmd.com/read/27912913/intravitreal-therapies-for-non-neovascular-age-related-macular-degeneration-with-intraretinal-or-subretinal-fluid
#2
M Cuesta-Lasso, A Vieira-Barros, R Dolz-Marco, M J Roig-Revert, J Badal, L Amselem, M Díaz-Llopis, R Gallego-Pinazo
OBJECTIVE: To evaluate the efficacy of intravitreal therapies in cases of atrophic age-related macular degeneration (AMD) with subretinal or intraretinal fluid. METHODS: A retrospective review was made of the clinical charts of patients diagnosed with atrophic AMD with subretinal or intraretinal fluid. Fundus photographs and spectral-domain optical coherence tomography images were examined, and an analysis was made on the presence of fluid and its density. Neovascularisation was ruled out by fluorescein and/or indocyanine green angiography...
November 29, 2016: Archivos de la Sociedad Española de Oftalmología
https://www.readbyqxmd.com/read/27909661/the-oblique-mattress-lasso-loop-stitch-for-arthroscopic-capsulolabral-repair
#3
Nata Parnes, Maryellen Blevins, Monica Morman, Paul Carey
Arthroscopic capsulolabral repair during shoulder stabilization surgery requires the use of suture anchors. Several arthroscopic suturing techniques for capsulolabral repair have been described, and each carries very specific advantages and disadvantages with regard to risk, patient satisfaction, and functional outcomes. The purpose of this report is to describe the oblique mattress lasso-loop stitch. This stitch (1) provides strong initial fixation of the labrum, (2) establishes labral height and allows for larger capsular plication if needed, (3) prevents the suture from cutting through the radial fibers of the glenoid labrum, (4) prevents knot migration to the articular side and loosening of the knot, and (5) requires fewer implants and preserves glenoid bone stock by increasing the amount of labrum and capsule that can be reattached to the glenoid with a single-loaded suture anchor...
October 2016: Arthroscopy Techniques
https://www.readbyqxmd.com/read/27899565/the-rrp6-c-terminal-domain-binds-rna-and-activates-the-nuclear-rna-exosome
#4
Elizabeth V Wasmuth, Christopher D Lima
The eukaryotic RNA exosome is an essential, multi-subunit complex that catalyzes RNA turnover, maturation, and quality control processes. Its non-catalytic donut-shaped core includes 9 subunits that associate with the 3' to 5' exoribonucleases Rrp6, and Rrp44/Dis3, a subunit that also catalyzes endoribonuclease activity. Although recent structures and biochemical studies of RNA bound exosomes from S. cerevisiae revealed that the Exo9 central channel guides RNA to either Rrp6 or Rrp44 using partially overlapping and mutually exclusive paths, several issues related to RNA recruitment remain...
November 29, 2016: Nucleic Acids Research
https://www.readbyqxmd.com/read/27896966/enforcing-co-expression-in-multimodal-regression-framework
#5
Pascal Zille, Vince D Calhoun, Yu-Ping Wang
We consider the problem of multimodal data integration for the study of complex neurological diseases (e.g. schizophrenia). Among the challenges arising in such situation, estimating the link between genetic and neurological variability within a population sample has been a promising direction. A wide variety of statistical models arose from such applications. For example, Lasso regression and its multitask extension are often used to fit a multivariate linear relationship between given phenotype(s) and associated observations...
2016: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/27896964/integrative-analysis-for-lung-adenocarcinoma-predicts-morphological-features-associated-with-genetic-variations
#6
Chao Wang, Hai Su, Lin Yang, Kun Huang
Lung cancer is one of the most deadly cancers and lung adenocarcinoma (LUAD) is the most common histological type of lung cancer. However, LUAD is highly heterogeneous due to genetic difference as well as phenotypic differences such as cellular and tissue morphology. In this paper, we systematically examine the relationships between histological features and gene transcription. Specifically, we calculated 283 morphological features from histology images for 201 LUAD patients from TCGA project and identified the morphological feature with strong correlation with patient outcome...
2016: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/27896962/adaptive-testing-of-snp-brain-functional-connectivity-association-via-a-modular-network-analysis
#7
Chen Gao, Junghi Kim, Wei Pan
Due to its high dimensionality and high noise levels, analysis of a large brain functional network may not be powerful and easy to interpret; instead, decomposition of a large network into smaller subcomponents called modules may be more promising as suggested by some empirical evidence. For example, alteration of brain modularity is observed in patients suffering from various types of brain malfunctions. Although several methods exist for estimating brain functional networks, such as the sample correlation matrix or graphical lasso for a sparse precision matrix, it is still difficult to extract modules from such network estimates...
2016: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/27893398/probabilistic-inference-on-multiple-normalized-genome-wide-signal-profiles-with-model-regularization
#8
Ka-Chun Wong, Chengbin Peng, Shankai Yan, Cheng Liang
Understanding genome-wide protein-DNA interactions forms the basis for further focused studies. In particular, the chromatin immunoprecipitation (ChIP) with sequencing (ChIPSeq) technology can enable us to measure the genome-wide occupancy of DNA-binding protein of interest in vivo. Multiple ChIP-Seq runs thus inherent the potential for us to decipher the combinatorial interactions among multiple DNA-binding proteins. To handle those multiple genome-wide runs, we propose to integrate regularized regression functions (i...
November 21, 2016: IEEE Transactions on Nanobioscience
https://www.readbyqxmd.com/read/27893385/nelasso-group-sparse-modeling-for-characterizing-relations-among-named-entities-in-news-articles
#9
Amara Tariq, Asim Karim, Hassan Foroosh
Named entities such as people, locations, and organizations play a vital role in characterizing online content. They often reflect information of interest and are frequently used in search queries. Although named entities can be detected reliably from textual content, extracting relations among them is more challenging, yet useful in various applications (e.g. news recommending systems). In this paper, we present a novel model and system for learning semantic relations among named entities from collections of news articles...
November 23, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/27889439/when-a-gold-standard-isn-t-so-golden-lack-of-prediction-of-subjective-sleep-quality-from-sleep-polysomnography
#10
Katherine A Kaplan, Jason Hirshman, Beatriz Hernandez, Marcia L Stefanick, Andrew R Hoffman, Susan Redline, Sonia Ancoli-Israel, Katie Stone, Leah Friedman, Jamie M Zeitzer
BACKGROUND: Reports of subjective sleep quality are frequently collected in research and clinical practice. It is unclear, however, how well polysomnographic measures of sleep correlate with subjective reports of prior-night sleep quality in elderly men and women. Furthermore, the relative importance of various polysomnographic, demographic and clinical characteristics in predicting subjective sleep quality is not known. We sought to determine the correlates of subjective sleep quality in older adults using more recently developed machine learning algorithms that are suitable for selecting and ranking important variables...
November 24, 2016: Biological Psychology
https://www.readbyqxmd.com/read/27886244/reconstructing-networks-from-profit-sequences-in-evolutionary-games-via-a-multiobjective-optimization-approach-with-lasso-initialization
#11
Kai Wu, Jing Liu, Shuai Wang
Evolutionary games (EG) model a common type of interactions in various complex, networked, natural and social systems. Given such a system with only profit sequences being available, reconstructing the interacting structure of EG networks is fundamental to understand and control its collective dynamics. Existing approaches used to handle this problem, such as the lasso, a convex optimization method, need a user-defined constant to control the tradeoff between the natural sparsity of networks and measurement error (the difference between observed data and simulated data)...
November 25, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27885853/nomogram-for-radiation-induced-hypothyroidism-prediction-in-nasopharyngeal-carcinoma-after-treatment
#12
Ren Luo, Mei Li, Zhining Yang, Yizhou Zhan, Baotian Huang, Jiayang Lu, Zhenxi Xu, Zhixiong Lin
OBJECTIVE: The aim of this study was to develop a nomogram for radiation-induced hypothyroidism (RHT) prediction. METHODS: We collected data from 164 NPC patients in our previous prospective study. Biochemical hypothyroidism (HT) was defined as a serum thyroid stimulating hormone (TSH) level greater than the normal value. We collected both clinical and dose-volume factors. A univariate Cox regression analysis was performed to identify RHT risk factors. Optimal predictors were selected according to the least absolute shrinkage and selection operator (LASSO)...
November 25, 2016: British Journal of Radiology
https://www.readbyqxmd.com/read/27879477/robust-group-fused-lasso-for-multisample-copy-number-variation-detection-under-uncertainty
#13
Hossein Sharifi Noghabi, Majid Mohammadi, Yao-Hua Tan
One of the most important needs in the post-genome era is providing the researchers with reliable and efficient computational tools to extract and analyse this huge amount of biological data, in which DNA copy number variation (CNV) is a vitally important one. Array-based comparative genomic hybridisation (aCGH) is a common approach in order to detect CNVs. Most of methods for this purpose were proposed for one-dimensional profiles. However, slightly this focus has moved from one- to multi-dimensional signals...
December 2016: IET Systems Biology
https://www.readbyqxmd.com/read/27875217/automatic-scoring-of-multiple-semantic-attributes-with-multi-task-feature-leverage-a-study-on-pulmonary-nodules-in-ct-images
#14
Sihong Chen, Jing Qin, Xing Ji, Baiying Lei, Tianfu Wang, Dong Ni, Jie-Zhi Cheng
The gap between the computational and semantic features is the one of major factors that bottlenecks the computer-aided diagnosis (CAD) performance from clinical usage. To bridge this gap, we exploit three multi-task learning (MTL) schemes to leverage heterogeneous computational features derived from deep learning models of stacked denoising autoencoder (SDAE) and convolutional neural network (CNN), as well as hand-crafted Haar-like and HoG features, for the description of 9 semantic features for lung nodules in CT images...
November 16, 2016: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/27874096/complex-lasso-new-entangled-motifs-in-proteins
#15
Wanda Niemyska, Pawel Dabrowski-Tumanski, Michal Kadlof, Ellinor Haglund, Piotr Sułkowski, Joanna I Sulkowska
We identify new entangled motifs in proteins that we call complex lassos. Lassos arise in proteins with disulfide bridges (or in proteins with amide linkages), when termini of a protein backbone pierce through an auxiliary surface of minimal area, spanned on a covalent loop. We find that as much as 18% of all proteins with disulfide bridges in a non-redundant subset of PDB form complex lassos, and classify them into six distinct geometric classes, one of which resembles supercoiling known from DNA. Based on biological classification of proteins we find that lassos are much more common in viruses, plants and fungi than in other kingdoms of life...
November 22, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27867012/a-robust-sparse-modeling-framework-for-estimating-schizophrenia-biomarkers-from-fmri
#16
Keith Dillon, Vince Calhoun, Yu-Ping Wang
BACKGROUND: Our goal is to identify the brain regions most relevant to mental illness using neuroimaging. State of the art machine learning methods commonly suffer from repeatability difficulties in this application, particularly when using large and heterogeneous populations for samples. NEW METHOD: We revisit both dimensionality reduction and sparse modeling, and recast them in a common optimization-based framework. This allows us to combine the benefits of both types of methods in an approach which we call unambiguous components...
November 17, 2016: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27862181/identification-of-biomarker-by-treatment-interactions-in-randomized-clinical-trials-with-survival-outcomes-and-high-dimensional-spaces
#17
Nils Ternès, Federico Rotolo, Georg Heinze, Stefan Michiels
Stratified medicine seeks to identify biomarkers or parsimonious gene signatures distinguishing patients that will benefit most from a targeted treatment. We evaluated 12 approaches in high-dimensional Cox models in randomized clinical trials: penalization of the biomarker main effects and biomarker-by-treatment interactions (full-lasso, three kinds of adaptive lasso, ridge+lasso and group-lasso); dimensionality reduction of the main effect matrix via linear combinations (PCA+lasso (where PCA is principal components analysis) or PLS+lasso (where PLS is partial least squares)); penalization of modified covariates or of the arm-specific biomarker effects (two-I model); gradient boosting; and univariate approach with control of multiple testing...
November 15, 2016: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/27858316/clinical-outcomes-linked-to%C3%A2-expression%C3%A2-of-gene-subsets-for-protein-hormones-and-their-cognate-receptors-from-lcm-procured-breast%C3%A2-carcinoma-cells
#18
Michael W Daniels, Guy N Brock, James L Wittliff
PURPOSE: Certain peptide hormones and/or their cognate receptors influencing normal cellular pathways also have been detected in breast cancers. The hypothesis is that gene subsets of these regulatory molecules predict risk of breast carcinoma recurrence in patients with primary disease. METHODS: Gene expression levels of 61 hormones and 81 receptors were determined by microarray with LCM-procured carcinoma cells of 247 de-identified biopsies. Univariable and multivariable Cox regressions were determined using expression levels of each hormone/receptor gene, individually or as a pair...
November 17, 2016: Breast Cancer Research and Treatment
https://www.readbyqxmd.com/read/27843566/exercise-restrictions-trigger-psychological-difficulty-in-active-and-athletic-adults-with-hypertrophic-cardiomyopathy
#19
Rebecca C Luiten, Kelly Ormond, Lisa Post, Irfan M Asif, Matthew T Wheeler, Colleen Caleshu
OBJECTIVE: We examined the extent and nature of the psychological difficulty experienced by athletic adults with hypertrophic cardiomyopathy (HCM), correlates of that difficulty and coping mechanisms. METHODS: A survey assessed athletic history and psychological impact of exercise restrictions. LASSO penalised linear regression identified factors associated with psychological difficulty. Semistructured interviews provided deeper insight into the nature and origins of psychological difficulty...
2016: Open Heart
https://www.readbyqxmd.com/read/27843486/efficient-regularized-regression-with-l0-penalty-for-variable-selection-and-network-construction
#20
Zhenqiu Liu, Gang Li
Variable selections for regression with high-dimensional big data have found many applications in bioinformatics and computational biology. One appealing approach is the L0 regularized regression which penalizes the number of nonzero features in the model directly. However, it is well known that L0 optimization is NP-hard and computationally challenging. In this paper, we propose efficient EM (L0EM) and dual L0EM (DL0EM) algorithms that directly approximate the L0 optimization problem. While L0EM is efficient with large sample size, DL0EM is efficient with high-dimensional (n ≪ m) data...
2016: Computational and Mathematical Methods in Medicine
keyword
keyword
78480
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"