scholarly journals Computational Identification of Lysine Glutarylation Sites Using Positive- Unlabeled Learning

2020 ◽  
Vol 21 (3) ◽  
pp. 204-211
Author(s):  
Zhe Ju ◽  
Shi-Yun Wang
Keyword(s):  
Crucial Role ◽  
Learning Algorithm ◽  
Biological Mechanisms ◽  
Bioinformatics Tool ◽  
Accurate Identification ◽  
Mitochondrial Functions ◽  
New Type ◽  
Computational Identification ◽  
User Friendly ◽  
Protein Acylation

Background: As a new type of protein acylation modification, lysine glutarylation has been found to play a crucial role in metabolic processes and mitochondrial functions. To further explore the biological mechanisms and functions of glutarylation, it is significant to predict the potential glutarylation sites. In the existing glutarylation site predictors, experimentally verified glutarylation sites are treated as positive samples and non-verified lysine sites as the negative samples to train predictors. However, the non-verified lysine sites may contain some glutarylation sites which have not been experimentally identified yet. Methods: In this study, experimentally verified glutarylation sites are treated as the positive samples, whereas the remaining non-verified lysine sites are treated as unlabeled samples. A bioinformatics tool named PUL-GLU was developed to identify glutarylation sites using a positive-unlabeled learning algorithm. Results: Experimental results show that PUL-GLU significantly outperforms the current glutarylation site predictors. Therefore, PUL-GLU can be a powerful tool for accurate identification of protein glutarylation sites. Conclusion: A user-friendly web-server for PUL-GLU is available at http://bioinform.cn/pul_glu/.

Recent Advances in Computational Methods for Identifying Anticancer Peptides

2019 ◽  
Vol 20 (5) ◽  
pp. 481-487 ◽  
Author(s):  
Pengmian Feng ◽  
Zhenyi Wang
Keyword(s):  
Computational Methods ◽  
Clinical Applications ◽  
Future Perspectives ◽  
Small Peptides ◽  
Accurate Identification ◽  
Normal Cells ◽  
Anticancer Peptide ◽  
Anticancer Peptides ◽  
Computational Identification ◽  
Reliable Methods

Anticancer peptide (ACP) is a kind of small peptides that can kill cancer cells without damaging normal cells. In recent years, ACP has been pre-clinically used for cancer treatment. Therefore, accurate identification of ACPs will promote their clinical applications. In contrast to labor-intensive experimental techniques, a series of computational methods have been proposed for identifying ACPs. In this review, we briefly summarized the current progress in computational identification of ACPs. The challenges and future perspectives in developing reliable methods for identification of ACPs were also discussed. We anticipate that this review could provide novel insights into future researches on anticancer peptides.

Dynamical Analysis of bantam-Regulated Drosophila Circadian Rhythm Model

2014 ◽  
Vol 24 (12) ◽  
pp. 1450161 ◽  
Author(s):  
Ying Li ◽  
Zengrong Liu
Keyword(s):  
Circadian Rhythm ◽  
Crucial Role ◽  
Target Genes ◽  
Classical Model ◽  
Dynamical Analysis ◽  
Biological Processes ◽  
Biological Mechanisms ◽  
Environmental Perturbations ◽  
Dynamical Behaviors ◽  
Important Regulator

MicroRNAs (miRNAs) interact with 3′untranslated region (UTR) elements of target genes to regulate mRNA stability or translation, and play a crucial role in regulating many different biological processes. bantam, a conserved miRNA, is involved in several functions, such as regulating Drosophila growth and circadian rhythm. Recently, it has been discovered that bantam plays a crucial role in the core circadian pacemaker. In this paper, based on experimental observations, a detailed dynamical model of bantam-regulated circadian clock system is developed to show the post-transcriptional behaviors in the modulation of Drosophila circadian rhythm, in which the regulation of bantam is incorporated into a classical model. The dynamical behaviors of the model are consistent with the experimental observations, which shows that bantam is an important regulator of Drosophila circadian rhythm. The sensitivity analysis of parameters demonstrates that with the regulation of bantam the system is more sensitive to perturbations, indicating that bantam regulation makes it easier for the organism to modulate its period against the environmental perturbations. The effectiveness in rescuing locomotor activity rhythms of mutated flies shows that bantam is necessary for strong and sustained rhythms. In addition, the biological mechanisms of bantam regulation are analyzed, which may help us more clearly understand Drosophila circadian rhythm regulated by other miRNAs.

Pl@ntwood: A Computer-Assisted Identification Tool for 110 species of amazon trees based on wood Anatomical Features

IAWA Journal ◽  
2011 ◽  
Vol 32 (2) ◽  
pp. 221-232 ◽  
Author(s):  
Carolina Sarmiento ◽  
Pierre Détienne ◽  
Christine Heinz ◽  
Jean-François Molino ◽  
Pierre Grard ◽  
...  
Keyword(s):  
Tree Species ◽  
Tropical Species ◽  
Computer Assisted ◽  
Accurate Identification ◽  
Anatomical Features ◽  
System A ◽  
Microscopic Features ◽  
On Line ◽  
User Friendly ◽  
Identification Tool

Sustainable management and conservation of tropical trees and forests require accurate identification of tree species. Reliable, user-friendly identification tools based on macroscopic morphological features have already been developed for various tree floras. Wood anatomical features provide also a considerable amount of information that can be used for timber traceability, certification and trade control. Yet, this information is still poorly used, and only a handful of experts are able to use it for plant species identification. Here, we present an interactive, user-friendly tool based on vector graphics, illustrating 99 states of 27 wood characters from 110 Amazonian tree species belonging to 34 families. Pl@ntWood is a graphical identification tool based on the IDAO system, a multimedia approach to plant identification. Wood anatomical characters were selected from the IAWA list of microscopic features for hardwood identification, which will enable us to easily extend this work to a larger number of species. A stand-alone application has been developed and an on-line version will be delivered in the near future. Besides allowing non-specialists to identify plants in a user-friendly interface, this system can be used with different purposes such as teaching, conservation, management, and selftraining in the wood anatomy of tropical species.

DeepYY1: a deep learning approach to identify YY1-mediated chromatin loops

2020 ◽  
Author(s):  
Fu-Ying Dao ◽  
Hao Lv ◽  
Dan Zhang ◽  
Zi-Mei Zhang ◽  
Li Liu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Computational Methods ◽  
Learning Algorithm ◽  
Cell Types ◽  
Chromatin Loops ◽  
Deep Learning Algorithm ◽  
Dna Elements ◽  
Chromatin Folding ◽  
User Friendly ◽  
Different Cell Types

Abstract The protein Yin Yang 1 (YY1) could form dimers that facilitate the interaction between active enhancers and promoter-proximal elements. YY1-mediated enhancer–promoter interaction is the general feature of mammalian gene control. Recently, some computational methods have been developed to characterize the interactions between DNA elements by elucidating important features of chromatin folding; however, no computational methods have been developed for identifying the YY1-mediated chromatin loops. In this study, we developed a deep learning algorithm named DeepYY1 based on word2vec to determine whether a pair of YY1 motifs would form a loop. The proposed models showed a high prediction performance (AUCs$\ge$0.93) on both training datasets and testing datasets in different cell types, demonstrating that DeepYY1 has an excellent performance in the identification of the YY1-mediated chromatin loops. Our study also suggested that sequences play an important role in the formation of YY1-mediated chromatin loops. Furthermore, we briefly discussed the distribution of the replication origin site in the loops. Finally, a user-friendly web server was established, and it can be freely accessed at http://lin-group.cn/server/DeepYY1.

scholarly journals A Smartphone-based Medication Self-management System with Real-time Medication Monitoring

2013 ◽  
Vol 04 (01) ◽  
pp. 37-52 ◽  
Author(s):  
Y. Uchimura ◽  
K. Omae ◽  
K. Waki ◽  
H. Fujita ◽  
K. Ohe ◽  
...  
Keyword(s):  
Real Time ◽  
Management System ◽  
Self Management ◽  
Prescription Data ◽  
Medication Regimen ◽  
Medication History ◽  
Medication Monitoring ◽  
Innovative Solution ◽  
New Type ◽  
User Friendly

SummaryBackground: Most patients cannot remember their entire medication regimen and occasionally forget to take their medication.Objectives: The objective of the study was to design, develop, and demonstrate the feasibility of a new type of medication self-management system using smartphones with real-time medication monitoring.Methods: We designed and developed a smartphone-based medication self-management system (SMSS) based on interviews of 116 patients. The system offered patients two main functions by means of smartphones: (1) storage and provision of an accurate, portable medication history and medication-taking records of patients; and (2) provision of a reminder to take medication only when the patient has forgotten to take his/her medication. These functions were realized by two data input methods: (a) reading of prescription data represented in two-dimensional barcodes using the smartphone camera and getting the photographic images of the pills; and (b) real-time medication monitoring by novel user-friendly wireless pillboxes.Results: Interviews suggested that a pocket-sized pillbox was demanded to support patient’s medication-taking outside the home and pillboxes for home use should be adaptable to the different means of pillbox storage. In accordance with the result, we designed and developed SMSS. Ten patients participated in the feasibility study. In 17 out of 47 cases (36.2%), patients took their medication upon being presented with reminders by the system. Correct medication-taking occur-rence was improved using this system.Conclusions: The SMSS is acceptable to patients and has the advantage of supporting ubiquitous medication self-management using a smartphone. We believe that the proposed system is feasible and provides an innovative solution to encourage medication self-management.Citation: Hayakawa M, Uchimura Y, Omae K, Waki K, Fujita H, Ohe K. A smartphone-based medication selfmanagement system with real-time medication monitoring. Appl Clin Inf 2013; 4: 37–52http://dx.doi.org/10.4338/ACI-2012-10-RA-0045

scholarly journals Analysis of Array-CGH Data Using the R and Bioconductor Software Suite

2009 ◽  
Vol 2009 ◽  
pp. 1-8 ◽  
Author(s):  
Winfried A. Hofmann ◽  
Anja Weigmann ◽  
Marcel Tauscher ◽  
Britta Skawran ◽  
Tim Focken ◽  
...  
Keyword(s):  
Array Cgh ◽  
Molecular Genetic ◽  
Comparative Genomic ◽  
Accurate Identification ◽  
Genome Wide ◽  
Versatile Tool ◽  
Breakpoint Detection ◽  
Dna Copy Number Alterations ◽  
User Friendly

Background. Array-based comparative genomic hybridization (array-CGH) is an emerging high-resolution and high-throughput molecular genetic technique that allows genome-wide screening for chromosome alterations. DNA copy number alterations (CNAs) are a hallmark of somatic mutations in tumor genomes and congenital abnormalities that lead to diseases such as mental retardation. However, accurate identification of amplified or deleted regions requires a sequence of different computational analysis steps of the microarray data.Results. We have developed a user-friendly and versatile tool for the normalization, visualization, breakpoint detection, and comparative analysis of array-CGH data which allows the accurate and sensitive detection of CNAs.Conclusion. The implemented option for the determination of minimal altered regions (MARs) from a series of tumor samples is a step forward in the identification of new tumor suppressor genes or oncogenes.

AMPpred: An On-Line Predictor Design for Automated AMP Recognition

2012 ◽  
Vol 229-231 ◽  
pp. 2276-2279
Author(s):  
Yu An Pan ◽  
Xuan Xiao ◽  
Pu Wang
Keyword(s):  
Cross Validation ◽  
Support Vector ◽  
Svm Classifier ◽  
Bioinformatics Tool ◽  
Physical Chemical ◽  
Novel Approach ◽  
Cross Covariance ◽  
On Line ◽  
Leave One Out ◽  
User Friendly

Antimicrobial peptides (AMP) are potent, broad spectrum antibiotics which demonstrate potential as novel therapeutic agents. Because it is both time-consuming and laborious to identify new AMPs by experiment, this paper tries to resolve this problem by pattern recognition. Two major contents included: Firstly, up to six kinds of physicochemical properties value are selected to code the AMP sequence as physical-chemical property matrix (PCM), then auto and cross covariance transformation is performed to extract features from the PCM for AMP sequence expression; Secondly, these feature vectors are input to a powerful Support Vector Machine (SVM) classifier for training and new query AMP recognition. For a newly constructed AMP benchmark dataset, the overall classification accuracy about 96% has been achieved through the rigorous Leave-One-Out cross-validation. For convenience, a user-friendly web server, AMPpred, has been established at http://icpr.jci.jx.cn/bioinfo/AMPpred. It is anticipated that this on-line predictor may become a useful bioinformatics tool for molecular biology and drug development. Also, its novel approach will further stimulate the development of predicting peptide attributes.

A New Type of Hybrid Learning Algorithm for Three-Layered Feed-Forward Neural Networks

2014 ◽  
Vol 1030-1032 ◽  
pp. 1627-1632
Author(s):  
Yun Jun Yu ◽  
Sui Peng ◽  
Zhi Chuan Wu ◽  
Peng Liang He
Keyword(s):  
Neural Networks ◽  
Learning Algorithm ◽  
Least Square Method ◽  
Hybrid Learning ◽  
Least Square ◽  
Feed Forward ◽  
Hybrid Learning Algorithm ◽  
Layer Function ◽  
Feed Forward Neural Networks ◽  
New Type

The problem of local minimum cannot be avoided when it comes to nonlinear optimization in the learning algorithm of neural network parameters, and the larger the optimization space is, the more obvious the problem becomes. This paper proposes a new type of hybrid learning algorithm for three-layered feed-forward neural networks. This algorithm is based on three-layered feed-forward neural networks with output layer function, namely linear function, combining a quasi Newton algorithm with adaptive decoupled step and momentum (QNADSM) and iterative least square method to export. Simulation proves that this hybrid algorithm has strong self-adaptive capability, small calculation amount and fast convergence speed. It is an effective engineer practical algorithm.

scholarly journals The Novel Quantitative Technique for Assessment of Gait Symmetry Using Advanced Statistical Learning Algorithm

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Jianning Wu ◽  
Bin Wu
Keyword(s):  
Statistical Learning ◽  
Learning Algorithm ◽  
Lower Limbs ◽  
Classification Method ◽  
Support Vector ◽  
Accurate Identification ◽  
Index Method ◽  
Gait Symmetry ◽  
Significant Difference ◽  
Gait Asymmetry

The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of small difference of similarity between lower limbs is considered the reorganization of their different probability distribution. The kinetic gait data of 60 participants were recorded using a strain gauge force platform during normal walking. The classification method is designed based on advanced statistical learning algorithm such as support vector machine algorithm for binary classification and is adopted to quantitatively evaluate gait symmetry. The experiment results showed that the proposed method could capture more intrinsic dynamic information hidden in gait variables and recognize the right-left gait patterns with superior generalization performance. Moreover, our proposed techniques could identify the small significant difference between lower limbs when compared to the traditional symmetry index method for gait. The proposed algorithm would become an effective tool for early identification of the elderly gait asymmetry in the clinical diagnosis.

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