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Predicting the subcellular location of apoptosis proteins based on recurrence quantification analysis and the Hilbertben Huang transform

Han Guo-Sheng,Yu Zu-Guo,Anh Vo,

中国物理 B , 2011,
Abstract: Apoptosis proteins play an important role in the development and homeostasis of an organism. The elucidation of the subcellular locations and functions of these proteins is helpful for understanding the mechanism of programmed cell death. In this paper, the recurrent quantification analysis, Hilbert-Huang transform methods, the maximum relevance and minimum redundancy method and support vector machine are used to predict the subcellular location of apoptosis proteins. The validation of the jackknife test suggests that the proposed method can improve the prediction accuracy of the subcellular location of apoptosis proteins and its application may be promising in other fields.
A Single Monitor Method for Voltage Sag Source Location using Hilbert Huang Transform
Wong Ling Ai,Hussain Shareef
Research Journal of Applied Sciences, Engineering and Technology , 2013,
Abstract: This study introduces a method for voltage sag source location based on Hilbert Huang transformed monitored current signal. Unlike the traditional method, the proposed method first transforms the recorded current during the sag event to obtain frequency-time plot (Hilbert spectra) and IMF plot before the location of voltage sag source is determined. Then based on the change in frequency and IMF the relative location of voltage sag source is obtained. The effectiveness of the proposed method has been verified through simulation on 20 bus system and by comparing with an existing S-Transform based method. The results show that the presented method can determine the location of voltage sag source correctly.
HybridGO-Loc: Mining Hybrid Features on Gene Ontology for Predicting Subcellular Localization of Multi-Location Proteins  [PDF]
Shibiao Wan, Man-Wai Mak, Sun-Yuan Kung
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0089545
Abstract: Protein subcellular localization prediction, as an essential step to elucidate the functions in vivo of proteins and identify drugs targets, has been extensively studied in previous decades. Instead of only determining subcellular localization of single-label proteins, recent studies have focused on predicting both single- and multi-location proteins. Computational methods based on Gene Ontology (GO) have been demonstrated to be superior to methods based on other features. However, existing GO-based methods focus on the occurrences of GO terms and disregard their relationships. This paper proposes a multi-label subcellular-localization predictor, namely HybridGO-Loc, that leverages not only the GO term occurrences but also the inter-term relationships. This is achieved by hybridizing the GO frequencies of occurrences and the semantic similarity between GO terms. Given a protein, a set of GO terms are retrieved by searching against the gene ontology database, using the accession numbers of homologous proteins obtained via BLAST search as the keys. The frequency of GO occurrences and semantic similarity (SS) between GO terms are used to formulate frequency vectors and semantic similarity vectors, respectively, which are subsequently hybridized to construct fusion vectors. An adaptive-decision based multi-label support vector machine (SVM) classifier is proposed to classify the fusion vectors. Experimental results based on recent benchmark datasets and a new dataset containing novel proteins show that the proposed hybrid-feature predictor significantly outperforms predictors based on individual GO features as well as other state-of-the-art predictors. For readers' convenience, the HybridGO-Loc server, which is for predicting virus or plant proteins, is available online at http://bioinfo.eie.polyu.edu.hk/HybridGo?Server/.
Nearest neighbour algorithm for predicting protein subcellular location


计算机应用研究 , 2007,
Abstract: Based on the amino acid composition of the proteins, the nearest neighbour algorithm by using three distance functions,i, e. , Euclidean distance, Minkowski distance and generalized distance, was developed for predicting the protein subcellular location. The results show that such an approach is novel, simple and effective.
Predicting the Function and Subcellular Location of Caenorhabditis elegans Proteins Similar to Saccharomyces cerevisiae -Oxidation Enzymes
Aner Gurvitz,Sigrid Langer,Martin Piskacek,Barbara Hamilton,Helmut Ruis,Andreas Hartig
Comparative and Functional Genomics , 2000, DOI: 10.1002/1097-0061(20000930)17:3<188::aid-yea27>3.0.co;2-e
Abstract: The role of peroxisomal processes in the maintenance of neurons has not been thoroughly investigated. We propose using Caenorhabditis elegans as a model organism for studying the molecular basis underlying neurodegeneration in certain human peroxisomal disorders, e.g. Zellweger syndrome, since the nematode neural network is well characterized and relatively simple in function. Here we have identified C. elegans PEX-5 (C34C6.6) representing the receptor for peroxisomal targeting signal type 1 (PTS1), defective in patients with such disorders. PEX-5 interacted strongly in a two-hybrid assay with Gal4p–SKL, and a screen using PEX-5 identified interaction partners that were predominantly terminated with PTS1 or its variants. A list of C. elegans proteins with similarities to well-characterized yeast β-oxidation enzymes was compiled by homology probing. The possible subcellular localization of these orthologues was predicted using an algorithm based on trafficking signals. Examining the C termini of selected nematode proteins for PTS1 function substantiated predictions made regarding the proteins' peroxisomal location. It is concluded that the eukaryotic PEX5-dependent route for importing PTS1-containing proteins into peroxisomes is conserved in nematodes. C. elegans might emerge as an attractive model system for studying the importance of peroxisomes and affiliated processes in neurodegeneration, and also for studying a β-oxidation process that is potentially compartmentalized in both mitochondria and peroxisomes.
New Hilbert-Huang transform associated with linear canonical transform

- , 2016,
Abstract: Hilbert-Huang变换是一种重要的非平稳信号分析工具,其对信号的处理包含两个方面:(i)经验模态分解;(ii)Hilbert谱分析. 2012年,Li,Tao和Wang利用线性正域上的Hilbert变换将该变换推广到线性正则域,从而获得了一种更为灵活的信号分析工具. 本文给出了Hilbert-Huang变换在线性正则域的另一种推广.
Hilbert-Huang transform is an efficient non-stationary signal analysis tool. In its processing, two aspects are included: (i) empirical mode decomposition; (ii) Hilbert spectral analysis. In 2012, Li, Tao and Wang proposed a generalized Hilbert-Huang transform associated the linear canonical transform, so as to obtain a more flexible tool. In this paper, a new Hilbert-Huang transform associated with the linear canonical transform is proposed
The application of Hilbert-Huang transform in transient signal detection

- , 2015, DOI: 10.16300/j.cnki.1000-3630.2015.02.013
Abstract: 空投物体入水时产生具有时域冲击特性的信号,一般称之为瞬态信号。Hilbert-Huang变换可通过经验模态分解和Hilbert谱分析两种方法,从时频角度对瞬态信号进行分析。介绍了Hilbert-Huang变换的基本原理,建立了瞬态信号的数学模型,提出了基于Hilbert-Huang变换的信号重构瞬态信号检测方法,并与传统能量检测器的性能进行了对比分析,最后通过软件仿真和湖试数据处理验证了该方法的可行性和有效性。
When an object airdropped into the water, some signals with impact characteristics in time domain will be generated, which are commonly known as transient signals. Hilbert-Huang Transform could analyze the transient signals in time-frequency domain by empirical mode decomposition and Hilbert spectral analysis. The principle of Hilbert-Huang Transform is introduced, and the mathematic model of transient signal is formed. A new method of transient signal detection based on Hilbert-Huang Transform is proposed, whose performance is analyzed and compared with that of the traditional energy detector. Finally the feasibility and validity of the method are verified by the software simulation and the data processing of lake experiment.
Cognitive Radio Sensing Using Hilbert Huang Transform  [PDF]
K. A. Narayanankutty, Abhijith A. Nair, Dilip Soori, Deepak Pradeep, V. Ravi Teja, Vishnu K.B.
Wireless Engineering and Technology (WET) , 2010, DOI: 10.4236/wet.2010.11006
Abstract: Vast segments of the frequency spectrum are reserved for primary (licensed) users. These legacy users often un-der-utilize their reserved spectrum thus causing bandwidth waste. The unlicensed (secondary) users can take advantage of this fact and exploit the spectral holes (vacant spectrum segments). Since spectrum occupancy is transient in nature it is imperative that the spectral holes are identified as fast as possible. To accomplish this, we propose a novel adaptive spectrum sensing procedure. This procedure scans a wideband spectrum using Hilbert Huang Transform and detects the spectral holes present in the spectrum.
Experimental Analysis of Complex Chaotic System by Hilbert-Huang Transform Usage
Josef Koke , Miroslav Kopecky
Acta Mechanica Slovaca , 2009, DOI: 10.2478/v10147-010-0040-2
Abstract: The paper demonstrates one promising algorithm for adaptive prediction of trajectory transitions between local basins of attraction of deterministic chaotic systems using Hilbert-Huang Transform. The expected transitions of higher dimensional chaotic systems are predicted by low order intrinsic modal functions, obtained from state variables by HHT. The behavior of chaotic systems in the state-space is transformed to system behavior in an approximated parameter-space obtained by Huang algorithm. Also a brief comparison to adaptive method using quadratic neural unit (QNU) with forcing inputs, introduced by Bukovsky [2], is shown.
Cutting force response in milling of Inconel: analysis by wavelet and Hilbert-Huang Transforms
Litak, Grzegorz;Kecik, Krzysztof;Rusinek, Rafal;
Latin American Journal of Solids and Structures , 2013, DOI: 10.1590/S1679-78252013000100013
Abstract: we study the milling process of inconel. by continuously increasing the cutting depth we follow the system response and appearance of oscillations of larger amplitude. the cutting force amplitude and frequency analysis has been done by means of wavelets and hilbert-huang transform. we report that in our system the force oscillations are closely related to the rotational motion of the tool and advocate for a regenerative mechanism of chatter vibrations. to identify vibrations amplitudes occurrence in time scale we apply wavelet and hilbert-huang transforms.
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