5,213 results match your criteria similarity matrix


KCRR: a nonlinear machine learning with a modified genomic similarity matrix improved the genomic prediction efficiency.

Brief Bioinform 2021 May 8. Epub 2021 May 8.

Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, P. R. China.

Nowadays, advances in high-throughput sequencing benefit the increasing application of genomic prediction (GP) in breeding programs. In this research, we designed a Cosine kernel-based KRR named KCRR to perform GP. This paper assessed the prediction accuracies of 12 traits with various heritability and genetic architectures from four populations using the genomic best linear unbiased prediction (GBLUP), BayesB, support vector regression (SVR), and KCRR. Read More

View Article and Full-Text PDF

Family with sequence similarity 83 member A promotes tumor cell proliferation and metastasis and predicts poor prognosis in cervical cancer.

Pathol Res Pract 2021 Apr 15;222:153450. Epub 2021 Apr 15.

Department of Obstetrics and Gynecology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China. Electronic address:

Family with sequence similarity 83 member A (FAM83A) is a member of the FAM83 family and is proven to have oncogenic properties in several cancers. However, the mechanisms of FAM83A in human cervical cancer (CC) progression are unknown. Here, we found that FAM83A is highly expressed in CC tissues and cell lines through western blot and qRT-PCR. Read More

View Article and Full-Text PDF

Clustering single-cell RNA-seq data by rank constrained similarity learning.

Bioinformatics 2021 May 7. Epub 2021 May 7.

Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC 28223, USA.

Motivation: Recent breakthroughs of single-cell RNA sequencing (scRNA-seq) technologies offer an exciting opportunity to identify heterogeneous cell types in complex tissues. However, the unavoidable biological noise and technical artifacts in scRNA-seq data as well as the high dimensionality of expression vectors make the problem highly challenging. Consequently, although numerous tools have been developed, their accuracy remains to be improved. Read More

View Article and Full-Text PDF

An Improved Similarity-Based Clustering Algorithm for Multi-Database Mining.

Entropy (Basel) 2021 Apr 29;23(5). Epub 2021 Apr 29.

School of Computer Science, Wuhan University, Wuhan 430072, China.

Clustering algorithms for multi-database mining (MDM) rely on computing (n2-n)/2 pairwise similarities between multiple databases to generate and evaluate m∈[1,(n2-n)/2] candidate clusterings in order to select the ideal partitioning that optimizes a predefined goodness measure. However, when these pairwise similarities are distributed around the mean value, the clustering algorithm becomes indecisive when choosing what database pairs are considered eligible to be grouped together. Consequently, a trivial result is produced by putting all the databases in one cluster or by returning singleton clusters. Read More

View Article and Full-Text PDF

Performance Comparison of Deep Learning Autoencoders for Cancer Subtype Detection Using Multi-Omics Data.

Cancers (Basel) 2021 Apr 22;13(9). Epub 2021 Apr 22.

Department of Computer Science, Virginia Commonwealth University, Richmond, VA 23284, USA.

A heterogeneous disease such as cancer is activated through multiple pathways and different perturbations. Depending upon the activated pathway(s), the survival of the patients varies significantly and shows different efficacy to various drugs. Therefore, cancer subtype detection using genomics level data is a significant research problem. Read More

View Article and Full-Text PDF

Robust Principal Component Thermography for Defect Detection in Composites.

Sensors (Basel) 2021 Apr 10;21(8). Epub 2021 Apr 10.

Computer Vision and Systems Laboratory (CVSL), Department of Electrical and Computer Engineering, Laval University, Quebec City, QC G1V 0A6, Canada.

Pulsed Thermography (PT) data are usually affected by noise and as such most of the research effort in the last few years has been directed towards the development of advanced signal processing methods to improve defect detection. Among the numerous techniques that have been proposed, principal component thermography (PCT)-based on principal component analysis (PCA)-is one of the most effective in terms of defect contrast enhancement and data compression. However, it is well-known that PCA can be significantly affected in the presence of corrupted data (e. Read More

View Article and Full-Text PDF

Cancer Subtype Recognition Based on Laplacian Rank Constrained Multiview Clustering.

Genes (Basel) 2021 Apr 3;12(4). Epub 2021 Apr 3.

School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China.

Integrating multigenomic data to recognize cancer subtype is an important task in bioinformatics. In recent years, some multiview clustering algorithms have been proposed and applied to identify cancer subtype. However, these clustering algorithms ignore that each data contributes differently to the clustering results during the fusion process, and they require additional clustering steps to generate the final labels. Read More

View Article and Full-Text PDF

Engineering a Highly Biomimetic Chitosan-Based Cartilage Scaffold by Using Short Fibers and a Cartilage-Decellularized Matrix.

Biomacromolecules 2021 Apr 29. Epub 2021 Apr 29.

College of Chemistry, Chemical Engineering & Biotechnology, Donghua University, Shanghai 201620, China.

Engineering scaffolds with structurally and biochemically biomimicking cues is essential for the success of tissue-engineered cartilage. Chitosan (CS)-based scaffolds have been widely used for cartilage regeneration due to its chemostructural similarity to the glycosaminoglycans (GAGs) found in the extracellular matrix of cartilage. However, the weak mechanical properties and inadequate chondroinduction capacity of CS give rise to compromised efficacy of cartilage regeneration. Read More

View Article and Full-Text PDF

Emerging evidence for kindlin oligomerization and its role in regulating kindlin function.

J Cell Sci 2021 Apr 20;134(8). Epub 2021 Apr 20.

School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore637551.

Integrin-mediated cell-extracellular matrix (ECM) interactions play crucial roles in a broad range of physiological and pathological processes. Kindlins are important positive regulators of integrin activation. The FERM-domain-containing kindlin family comprises three members, kindlin-1, kindlin-2 and kindlin-3 (also known as FERMT1, FERMT2 and FERMT3), which share high sequence similarity (identity >50%), as well as domain organization, but exhibit diverse tissue-specific expression patterns and cellular functions. Read More

View Article and Full-Text PDF

SMALF: miRNA-disease associations prediction based on stacked autoencoder and XGBoost.

BMC Bioinformatics 2021 Apr 28;22(1):219. Epub 2021 Apr 28.

School of Computer Science and Engineering, Central South University, Hunan, 410083, China.

Background: Identifying miRNA and disease associations helps us understand disease mechanisms of action from the molecular level. However, it is usually blind, time-consuming, and small-scale based on biological experiments. Hence, developing computational methods to predict unknown miRNA and disease associations is becoming increasingly important. Read More

View Article and Full-Text PDF

A computational approach to aid clinicians in selecting anti-viral drugs for COVID-19 trials.

Sci Rep 2021 04 27;11(1):9047. Epub 2021 Apr 27.

Department of CSE, IIIT-Delhi, New Delhi, 110020, India.

The year 2020 witnessed a heavy death toll due to COVID-19, calling for a global emergency. The continuous ongoing research and clinical trials paved the way for vaccines. But, the vaccine efficacy in the long run is still questionable due to the mutating coronavirus, which makes drug re-positioning a reasonable alternative. Read More

View Article and Full-Text PDF

MR to ultrasound image registration with segmentation-based learning for HDR prostate brachytherapy.

Med Phys 2021 Apr 27. Epub 2021 Apr 27.

Department of Radiation Oncology, Stanford University, Stanford, 94305, USA.

Purpose: Propagation of contours from high-quality magnetic resonance (MR) images to treatment planning ultrasound (US) images with severe needle artifacts is a challenging task, which can greatly aid the organ contouring in high dose rate (HDR) prostate brachytherapy. In this study, a deep learning approach was developed to automatize this registration procedure for HDR brachytherapy practice.

Methods: Because of the lack of training labels and difficulty of accurate registration from inferior image quality, a new segmentation-based registration framework was proposed for this multi-modality image registration problem. Read More

View Article and Full-Text PDF

PMDFI: Predicting miRNA-Disease Associations Based on High-Order Feature Interaction.

Front Genet 2021 9;12:656107. Epub 2021 Apr 9.

School of Computer Science and Engineering, Central South University, Changsha, China.

MicroRNAs (miRNAs) are non-coding RNA molecules that make a significant contribution to diverse biological processes, and their mutations and dysregulations are closely related to the occurrence, development, and treatment of human diseases. Therefore, identification of potential miRNA-disease associations contributes to elucidating the pathogenesis of tumorigenesis and seeking the effective treatment method for diseases. Due to the expensive cost of traditional biological experiments of determining associations between miRNAs and diseases, increasing numbers of effective computational models are being used to compensate for this limitation. Read More

View Article and Full-Text PDF

Extended similarity indices: the benefits of comparing more than two objects simultaneously. Part 2: speed, consistency, diversity selection.

J Cheminform 2021 Apr 23;13(1):33. Epub 2021 Apr 23.

Plasma Chemistry Research Group, Research Centre for Natural Sciences, Magyar tudósok krt. 2, 1117, Budapest, Hungary.

Despite being a central concept in cheminformatics, molecular similarity has so far been limited to the simultaneous comparison of only two molecules at a time and using one index, generally the Tanimoto coefficent. In a recent contribution we have not only introduced a complete mathematical framework for extended similarity calculations, (i.e. Read More

View Article and Full-Text PDF

MiRNA-disease association prediction via hypergraph learning based on high-dimensionality features.

BMC Med Inform Decis Mak 2021 04 20;21(Suppl 1):133. Epub 2021 Apr 20.

School of Computer Science and Technology, Anhui University, Hefei, China.

Background: MicroRNAs (miRNAs) have been confirmed to have close relationship with various human complex diseases. The identification of disease-related miRNAs provides great insights into the underlying pathogenesis of diseases. However, it is still a big challenge to identify which miRNAs are related to diseases. Read More

View Article and Full-Text PDF

Intrachain interaction topology can identify functionally similar intrinsically disordered proteins.

Biophys J 2021 Apr 15. Epub 2021 Apr 15.

Department of Physics and Astronomy, University of Denver, Denver, Colorado. Electronic address:

Functionally similar IDPs (intrinsically disordered proteins) often have little sequence similarity. This is in stark contrast to folded proteins and poses a challenge for the inverse problem, functional classification of IDPs using sequence alignment. The problem is further compounded because of the lack of structure in IDPs, preventing structural alignment as an alternate tool for classification. Read More

View Article and Full-Text PDF

Learning Log-Determinant Divergences for Positive Definite Matrices.

IEEE Trans Pattern Anal Mach Intell 2021 Apr 15;PP. Epub 2021 Apr 15.

Representations in the form of Symmetric Positive Definite (SPD) matrices have been popularized in a variety of visual learning applications due to their demonstrated ability to capture rich second-order statistics of visual data. There exist several similarity measures for comparing SPD matrices with documented benefits. However, selecting an appropriate measure for a given problem remains a challenge and in most cases, is the result of a trial-and-error process. Read More

View Article and Full-Text PDF

Drug-Target Interaction Prediction via Dual Laplacian Graph Regularized Logistic Matrix Factorization.

Biomed Res Int 2021 26;2021:5599263. Epub 2021 Mar 26.

Department of Pharmacy, Lianshui People's Hospital Affiliated to Kangda College, Nanjing Medical University, Huai'an 223300, China.

Drug-target interactions provide useful information for biomedical drug discovery as well as drug development. However, it is costly and time consuming to find drug-target interactions by experimental methods. As a result, developing computational approaches for this task is necessary and has practical significance. Read More

View Article and Full-Text PDF

Ethnobotanical Study of Medicinal Plants Used to Treat Human and Livestock Ailments in Hulet Eju Enese Woreda, East Gojjam Zone of Amhara Region, Ethiopia.

Evid Based Complement Alternat Med 2021 29;2021:6668541. Epub 2021 Mar 29.

College of Natural and Computational Sciences, Department of Biology, Salale University, Fiche, Ethiopia.

Indigenous people of a given community have their own local specific knowledge on plant use, management, and conservation. The objective of this study was to document medicinal plants used to treat human and livestock ailments in Hulet Eju Enese Woreda. The data were collected using semistructured interviews, focus group discussions, and field observations with local people. Read More

View Article and Full-Text PDF

Genetic changes are introduced by repeated exposure of Salmonella spiked in low water activity and high fat matrix to heat.

Sci Rep 2021 Apr 14;11(1):8144. Epub 2021 Apr 14.

Nestlé Research, Vers-Chez-les-Blanc 26, 1000, Lausanne, Switzerland.

WGS is used to define if isolates are "in" or "out" of an outbreak and/or microbial root cause investigation. No threshold of genetic differences is fixed and the conclusions on similarity between isolates are mainly based on the knowledge generated from previous outbreak investigations and reported mutation rates. Mutation rates in Salmonella when exposed to food processing conditions are lacking. Read More

View Article and Full-Text PDF

Sequence similarity in 3D for comparison of protein families.

J Mol Graph Model 2021 Mar 23;106:107906. Epub 2021 Mar 23.

Department of Biochemistry and Immunology, Federal University of Minas Gerais, Belo Horizonte, 31270-901, Brazil. Electronic address:

Homologous proteins are often compared by pairwise sequence alignment, and structure superposition if the atomic coordinates are available. Unification of sequence and structure data is an important task in structural biology. Here, we present the Sequence Similarity 3D (SS3D) method of integrating sequence and structure information. Read More

View Article and Full-Text PDF

EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture.

G3 (Bethesda) 2021 Apr;11(4)

Department of Genetics, 'Luiz de Queiroz' Agriculture College, University of São Paulo, São Paulo, Brazil.

Envirotyping is an essential technique used to unfold the nongenetic drivers associated with the phenotypic adaptation of living organisms. Here, we introduce the EnvRtype R package, a novel toolkit developed to interplay large-scale envirotyping data (enviromics) into quantitative genomics. To start a user-friendly envirotyping pipeline, this package offers: (1) remote sensing tools for collecting (get_weather and extract_GIS functions) and processing ecophysiological variables (processWTH function) from raw environmental data at single locations or worldwide; (2) environmental characterization by typing environments and profiling descriptors of environmental quality (env_typing function), in addition to gathering environmental covariables as quantitative descriptors for predictive purposes (W_matrix function); and (3) identification of environmental similarity that can be used as an enviromic-based kernel (env_typing function) in whole-genome prediction (GP), aimed at increasing ecophysiological knowledge in genomic best-unbiased predictions (GBLUP) and emulating reaction norm effects (get_kernel and kernel_model functions). Read More

View Article and Full-Text PDF

On solution existence of MHD Casson nanofluid transportation across an extending cylinder through porous media and evaluation of priori bounds.

Sci Rep 2021 Apr 8;11(1):7799. Epub 2021 Apr 8.

Department of Law, Economics and Human Sciences & Decisions Lab, University Mediterranea of Reggio Calabria, Reggio Calabria, Italy.

It is a theoretical exportation for mass transpiration and thermal transportation of Casson nanofluid over an extending cylindrical surface. The Stagnation point flow through porous matrix is influenced by magnetic field of uniform strength. Appropriate similarity functions are availed to yield the transmuted system of leading differential equations. Read More

View Article and Full-Text PDF

LINflow: a computational pipeline that combines an alignment-free with an alignment-based method to accelerate generation of similarity matrices for prokaryotic genomes.

PeerJ 2021 24;9:e10906. Epub 2021 Mar 24.

School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA, USA.

Background: Computing genomic similarity between strains is a prerequisite for genome-based prokaryotic classification and identification. Genomic similarity was first computed as Average Nucleotide Identity (ANI) values based on the alignment of genomic fragments. Since this is computationally expensive, faster and computationally cheaper alignment-free methods have been developed to estimate ANI. Read More

View Article and Full-Text PDF

A comparison of 71 binary similarity coefficients: The effect of base rates.

PLoS One 2021 7;16(4):e0247751. Epub 2021 Apr 7.

Department of Psychological Sciences, University of Missouri, Columbia, Missouri, United States of America.

There are many psychological applications that require collapsing the information in a two-mode (e.g., respondents-by-attributes) binary matrix into a one-mode (e. Read More

View Article and Full-Text PDF

In vitro comparison of harvesting site effects on cardiac extracellular matrix hydrogels.

J Biomed Mater Res A 2021 Apr 6. Epub 2021 Apr 6.

Department of Bioengineering, University of Texas at Arlington, Arlington, Texas, USA.

Cardiac extracellular matrix (cECM) derived hydrogel has been investigated to treat myocardial infarction through animal studies and clinical trials. The tissue harvesting site commonly selects porcine left ventricle (LV) because heart attack majorly takes place in LV. However, little is known about whether the region of cardiac tissue harvesting is critical for downstream applications. Read More

View Article and Full-Text PDF

Survey on graph embeddings and their applications to machine learning problems on graphs.

PeerJ Comput Sci 2021 4;7:e357. Epub 2021 Feb 4.

Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.

Dealing with relational data always required significant computational resources, domain expertise and task-dependent feature engineering to incorporate structural information into a predictive model. Nowadays, a family of automated graph feature engineering techniques has been proposed in different streams of literature. So-called graph embeddings provide a powerful tool to construct vectorized feature spaces for graphs and their components, such as nodes, edges and subgraphs under preserving inner graph properties. Read More

View Article and Full-Text PDF
February 2021

Hyaluronic Acid and a Short Peptide Improve the Performance of a PCL Electrospun Fibrous Scaffold Designed for Bone Tissue Engineering Applications.

Int J Mol Sci 2021 Mar 12;22(5). Epub 2021 Mar 12.

The Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv 6997801, Israel.

Bone tissue engineering is a rapidly developing, minimally invasive technique for regenerating lost bone with the aid of biomaterial scaffolds that mimic the structure and function of the extracellular matrix (ECM). Recently, scaffolds made of electrospun fibers have aroused interest due to their similarity to the ECM, and high porosity. Hyaluronic acid (HA) is an abundant component of the ECM and an attractive material for use in regenerative medicine; however, its processability by electrospinning is poor, and it must be used in combination with another polymer. Read More

View Article and Full-Text PDF

Collagen-Based Electrospun Materials for Tissue Engineering: A Systematic Review.

Bioengineering (Basel) 2021 Mar 18;8(3). Epub 2021 Mar 18.

Department of Materials Science and Engineering, The Ohio State University, Columbus, OH 43210, USA.

Collagen is a key component of the extracellular matrix (ECM) in organs and tissues throughout the body and is used for many tissue engineering applications. Electrospinning of collagen can produce scaffolds in a wide variety of shapes, fiber diameters and porosities to match that of the native ECM. This systematic review aims to pool data from available manuscripts on electrospun collagen and tissue engineering to provide insight into the connection between source material, solvent, crosslinking method and functional outcomes. Read More

View Article and Full-Text PDF

Novel Hydrogel Scaffolds Based on Alginate, Gelatin, 2-Hydroxyethyl Methacrylate, and Hydroxyapatite.

Polymers (Basel) 2021 Mar 18;13(6). Epub 2021 Mar 18.

Faculty of Technology and Metallurgy, University of Belgrade, Karnegijeva 4, 11000 Belgrade, Serbia.

Hydrogel scaffolding biomaterials are one of the most attractive polymeric biomaterials for regenerative engineering and can be engineered into tissue mimetic scaffolds to support cell growth due to their similarity to the native extracellular matrix. The novel, versatile hydrogel scaffolds based on alginate, gelatin, 2-hydroxyethyl methacrylate, and inorganic agent hydroxyapatite were prepared by modified cryogelation. The chemical composition, morphology, porosity, mechanical properties, effects on cell viability, in vitro degradation, in vitro and in vivo biocompatibility were tested to correlate the material's composition with the corresponding properties. Read More

View Article and Full-Text PDF