jackknife

WordNet

dive into the water bending the body at the waist at a right angle, like a jackknife
a dive in which the diver bends to touch the ankles before straightening out
black-and-white drumfish with an erect elongated dorsal fin (同)Equetus lanceolatus

PrepTutorEJDIC

(また『clasp knife』)ジャックナイフ(刃のたためる大型のポケットナイフ) / えび型飛込み,ジャックナイフダイブ / (トラクター・トレーラーなどが)まん中でVの字に折れ曲がる

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出典(authority):フリー百科事典『ウィキペディア（Wikipedia）』「2015/11/16 23:41:50」(JST)

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English Journal

Prediction of protein structure classes using hybrid space of multi-profile Bayes and bi-gram probability feature spaces.

Hayat M1, Tahir M2, Khan SA3.Author information 1Department of Computer Science, Abdul Wali Khan University Mardan, Pakistan. Electronic address: m.hayat@awkum.edu.pk.2Department of Computer Science, National University of Computer and Emerging Science, Peshawar, Pakistan.3Department of Computer Science, Abdul Wali Khan University Mardan, Pakistan.AbstractProteins are the executants of biological functions in living organisms. Comprehension of protein structure is a challenging problem in the era of proteomics, computational biology, and bioinformatics because of its pivotal role in protein folding patterns. Owing to the large exploration of protein sequences in protein databanks and intricacy of protein structures, experimental and theoretical methods are insufficient for prediction of protein structure classes. Therefore, it is highly desirable to develop an accurate, reliable, and high throughput computational model to predict protein structure classes correctly from polygenetic sequences. In this regard, we propose a promising model employing hybrid descriptor space in conjunction with optimized evidence-theoretic K-nearest neighbor algorithm. Hybrid space is the composition of two descriptor spaces including Multi-profile Bayes and bi-gram probability. In order to enhance the generalization power of the classifier, we have selected high discriminative descriptors from the hybrid space using particle swarm optimization, a well-known evolutionary feature selection technique. Performance evaluation of the proposed model is performed using the jackknife test on three low similarity benchmark datasets including 25PDB, 1189, and 640. The success rates of the proposed model are 87.0%, 86.6%, and 88.4%, respectively on the three benchmark datasets. The comparative analysis exhibits that our proposed model has yielded promising results compared to the existing methods in the literature. In addition, our proposed prediction system might be helpful in future research particularly in cases where the major focus of research is on low similarity datasets.
Journal of theoretical biology.J Theor Biol.2014 Apr 7;346:8-15. doi: 10.1016/j.jtbi.2013.12.015. Epub 2013 Dec 30.
Proteins are the executants of biological functions in living organisms. Comprehension of protein structure is a challenging problem in the era of proteomics, computational biology, and bioinformatics because of its pivotal role in protein folding patterns. Owing to the large exploration of protein
PMID 24384128

A hybrid method for prediction and repositioning of drug Anatomical Therapeutic Chemical classes.

Chen L1, Lu J, Zhang N, Huang T, Cai YD.Author information 1College of Information Engineering, Shanghai Maritime University, Shanghai 201306, People's Republic of China. chen_lei1@163.com.AbstractIn the Anatomical Therapeutic Chemical (ATC) classification system, therapeutic drugs are divided into 14 main classes according to the organ or system on which they act and their chemical, pharmacological and therapeutic properties. This system, recommended by the World Health Organization (WHO), provides a global standard for classifying medical substances and serves as a tool for international drug utilization research to improve quality of drug use. In view of this, it is necessary to develop effective computational prediction methods to identify the ATC-class of a given drug, which thereby could facilitate further analysis of this system. In this study, we initiated an attempt to develop a prediction method and to gain insights from it by utilizing ontology information of drug compounds. Since only about one-fourth of drugs in the ATC classification system have ontology information, a hybrid prediction method combining the ontology information, chemical interaction information and chemical structure information of drug compounds was proposed for the prediction of drug ATC-classes. As a result, by using the Jackknife test, the 1st prediction accuracies for identifying the 14 main ATC-classes in the training dataset, the internal validation dataset and the external validation dataset were 75.90%, 75.70% and 66.36%, respectively. Analysis of some samples with false-positive predictions in the internal and external validation datasets indicated that some of them may even have a relationship with the false-positive predicted ATC-class, suggesting novel uses of these drugs. It was conceivable that the proposed method could be used as an efficient tool to identify ATC-classes of novel drugs or to discover novel uses of known drugs.
Molecular bioSystems.Mol Biosyst.2014 Apr 4;10(4):868-77. doi: 10.1039/c3mb70490d. Epub 2014 Feb 4.
In the Anatomical Therapeutic Chemical (ATC) classification system, therapeutic drugs are divided into 14 main classes according to the organ or system on which they act and their chemical, pharmacological and therapeutic properties. This system, recommended by the World Health Organization (WHO), p
PMID 24492783

Detection of recurrent hepatocellular carcinoma on post-operative surveillance: comparison of MDCT and gadoxetic acid-enhanced MRI.

Kim KA1, Kim MJ, Choi JY, Park MS, Lim JS, Chung YE, Kim KW.Author information 1Department of Radiology, St. Vincent's Hospital, The Catholic University of Korea, Gyeonggi-do, South Korea.AbstractOBJECTIVE: To compare the accuracy of multidetector computed tomography (MDCT) and gadoxetic acid-enhanced magnetic resonance imaging (MRI) for the detection of intrahepatic tumor recurrence after curative resection of hepatocellular carcinoma (HCC).
Abdominal imaging.Abdom Imaging.2014 Apr;39(2):291-9. doi: 10.1007/s00261-013-0064-y.
OBJECTIVE: To compare the accuracy of multidetector computed tomography (MDCT) and gadoxetic acid-enhanced magnetic resonance imaging (MRI) for the detection of intrahepatic tumor recurrence after curative resection of hepatocellular carcinoma (HCC).MATERIALS AND METHODS: Fifty-six patients who unde
PMID 24384804

A Free-response Evaluation Determining Value in the Computed Tomography Attenuation Correction Image for Revealing Pulmonary Incidental Findings: A Phantom Study.

Thompson JD1, Hogg P2, Manning DJ3, Szczepura K2, Chakraborty DP4.Author information 1University of Salford, Directorate of Radiography, 6th Floor Allerton Building, Frederick Road Campus, Greater Manchester, M6 6PU, UK; University Hospitals of Morecambe Bay NHS Foundation Trust, Nuclear Medicine, Furness General Hospital, Dalton Lane, Barrow-in-Furness, Cumbria, LA14 4LF, UK. Electronic address: john.thompson@mbht.nhs.uk.2University of Salford, Directorate of Radiography, 6th Floor Allerton Building, Frederick Road Campus, Greater Manchester, M6 6PU, UK.3Lancaster Medical School, Faculty of Health & Medicine, Furness College, Lancaster University, Lancaster LA1 4YG, UK.4Medical Image Interpretation Assessment Laboratory, University of Pittsburgh, Presby South Tower, Room 4771, 200 Lothrop Street, Pittsburgh, PA 15213, USA.AbstractRATIONALE AND OBJECTIVES: The purpose of this study was to compare lesion-detection performance when interpreting computed tomography (CT) images that are acquired for attenuation correction when performing single photon emission computed tomography/computed tomography (SPECT/CT) myocardial perfusion studies. In the United Kingdom, there is a requirement that these images be interpreted; thus, it is necessary to understand observer performance on these images.
Academic radiology.Acad Radiol.2014 Apr;21(4):538-45. doi: 10.1016/j.acra.2014.01.003.
RATIONALE AND OBJECTIVES: The purpose of this study was to compare lesion-detection performance when interpreting computed tomography (CT) images that are acquired for attenuation correction when performing single photon emission computed tomography/computed tomography (SPECT/CT) myocardial perfusio
PMID 24594424

Japanese Journal

USING IMPROVED LOCALLY LINEAR EMBEDDING FOR PREDICTING PROTEIN STRUCTURAL CLASS

WEI PENG,WANG KAI,MA JUNWEI [他]
ICIC express letters. Part B, Applications : an international journal of research and surveys 3(6), 1363-1370, 2012-12
NAID 40019515965

極値分布関数の適合度評価に関する検討

藤部文昭
天気 58(9), 765-775, 2011-09-30
極値統計解析において,複数の確率分布の中からデータに適合するものを選ぶという方法が使われることがある.このようなアプローチの有効性を調べるため,Gumbel分布などに従う母集団からデータを抽出し,これに5つの極値分布関数のそれぞれを当てはめて推定した再現期待値のバイアスと不確定幅(推定幅)を,モンテカルロ・シミュレーションで評価した.その結果,パラメーター2個の分布(Gumbel分布など)は,母集 …
NAID 110008750221

肺腺癌ファントムを用いたソフトコピー(LCD)とハードコピー (Film) の病変検出能の比較

望月安雄,阿部慎司,門間正彦,山口弘次郎,安達登志樹
日本放射線技術學會雜誌 67(4), 328-335, 2011-04-20
… A two-tailed paired t-test and the jackknife method (parametric methods) were performed, and no significant differences were found in the area under the ROC curve (AUC) for the pulmonary fields, lungs, ribs, or mediastinum between the film and LCD display systems, and the detectability did not differ between the film and LCD monitors. …
NAID 10027963718

ROC解析における Jackknife 法を用いた観察者間変動の解析

鈴木信昭,清野和絵
日本放射線技術學會雜誌 66(11), 1492-1496, 2010-11-20
… The DBM MRMC—i.e., the software for analyze of statistically significant differences by the Jackknife method—was used. …
NAID 10026964972

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