• Bulletin of the Korean Chemical Society
• /
• 제33권4호
• /
• pp.1123-1127
• /
• 2012

P-gp (P-glycoprotein) is a member of the ATP binding cassette (ABC) family of transporters. It transports many kinds of anticancer drugs out of the cell. It plays a major role as a cause of multidrug resistance (MDR). MDR function may be a cause of the failure of chemotherapy in cancer and influence pharmacokinetic properties of many drugs. Hence classification of candidate drugs as substrates or nonsubstrate of the P-gp is important in drug development. Therefore to identify whether a compound is a P-gp substrate or not, in silico method is promising. Recursive Partitioning (RP) method was explored for prediction of P-gp substrate. A set of 261 compounds, including 146 substrates and 115 nonsubstrates of P-gp, was used to training and validation. Using molecular descriptors that we can interpret their own meaning, we have established two models for prediction of P-gp substrates. In the first model, we chose only 6 descriptors which have simple physical meaning. In the training set, the overall predictability of our model is 78.95%. In case of test set, overall predictability is 69.23%. Second model with 2D and 3D descriptors shows a little better predictability (overall predictability of training set is 79.29%, test set is 79.37%), the second model with 2D and 3D descriptors shows better discriminating power than first model with only 2D descriptors. This approach will be used to reduce the number of compounds required to be run in the P-gp efflux assay.

• Journal of Information Processing Systems
• /
• 제16권2호
• /
• pp.343-359
• /
• 2020

In this paper, a new algorithm is proposed for three-dimensional (3D) shape recognition using local features of model views and its sparse representation. The algorithm starts with the normalization of 3D models and the extraction of 2D views from uniformly distributed viewpoints. Consequently, the 2D views are stacked over each other to from view cubes. The algorithm employs the descriptors of 3D local features in the view cubes after applying Gabor filters in various directions as the initial features for 3D shape recognition. In the training stage, we store some 3D local features to build the prototype dictionary of local features. To extract an intermediate feature vector, we measure the similarity between the local descriptors of a shape model and the local features of the prototype dictionary. We represent the intermediate feature vectors of 3D models in the sparse domain to obtain the final descriptors of the models. Finally, support vector machine classifiers are used to recognize the 3D models. Experimental results using the Princeton Shape Benchmark database showed the average recognition rate of 89.7% using 20 views. We compared the proposed approach with state-of-the-art approaches and the results showed the effectiveness of the proposed algorithm.

• 한국수학교육학회지시리즈D:수학교육연구
• /
• 제15권1호
• /
• pp.81-91
• /
• 2011

The aim of this study was to explore the grade 1-3 students' geometrical thinking level descriptors based on van Hiele level descriptors. The data were collected through collection of geometric curriculum materials such as indicators and learning standards in Basic Education Core Curriculum and mathematics textbook for grades 1-3. The findings were found that 1) Inconsistency between descriptors appeared on mathematics curriculum and Thai mathematics textbooks. 2) Using topics on textbooks as criterion for exploring 5 of 7 descriptors appeared on Thai mathematics textbook indicated geometrical thinking levels based on van Hiele's model merely level 0 (Visualization) across textbooks for grades 1-3.

• Journal of Information Processing Systems
• /
• 제12권3호
• /
• pp.468-488
• /
• 2016

The paper proposes a novel framework for 3D face verification using dimensionality reduction based on highly distinctive local features in the presence of illumination and expression variations. The histograms of efficient local descriptors are used to represent distinctively the facial images. For this purpose, different local descriptors are evaluated, Local Binary Patterns (LBP), Three-Patch Local Binary Patterns (TPLBP), Four-Patch Local Binary Patterns (FPLBP), Binarized Statistical Image Features (BSIF) and Local Phase Quantization (LPQ). Furthermore, experiments on the combinations of the four local descriptors at feature level using simply histograms concatenation are provided. The performance of the proposed approach is evaluated with different dimensionality reduction algorithms: Principal Component Analysis (PCA), Orthogonal Locality Preserving Projection (OLPP) and the combined PCA+EFM (Enhanced Fisher linear discriminate Model). Finally, multi-class Support Vector Machine (SVM) is used as a classifier to carry out the verification between imposters and customers. The proposed method has been tested on CASIA-3D face database and the experimental results show that our method achieves a high verification performance.

• Advances in nano research
• /
• 제13권2호
• /
• pp.121-134
• /
• 2022

Emerge of nanotechnology impacts all aspects of humans' life. One of important aspects of the nanotechnology and nanoparticles (NPs) is in the food production industry. The safety of such foods is not well recognized and producing safe foods using nanoparticles involves delicate experiments. In this study, we aim to incorporate intelligent computer simulation in predicting safety degree of nanofoods. In this regard, the safety concerns on the nano-foods are addressed considering cytotoxicity levels in metal oxides nanoparticles using adaptive neuro-fuzzy inference system (ANFIS) and response surface method (RSM). Three descriptors including chemical bond length, lattice energy and enthalpy of formation gaseous cation of 15 selected NPs are examined to find their influence on the cytotoxicity of NPs. The most effective descriptor is selected using RSM method and dependency of the toxicity of these NPs on the descriptors are presented in 2D and 3D graphs obtained using ANFIS technique. A comprehensive parameters study is conducted to observe effects of different descriptors on cytotoxicity of NPs. The results indicated that combinations of descriptors have the most effects on the cytotoxicity.

• Journal of Information Processing Systems
• /
• 제14권1호
• /
• pp.176-190
• /
• 2018

This paper presents a novel convolutional neural network based multi-feature fusion learning method for non-rigid 3D model retrieval, which can investigate the useful discriminative information of the heat kernel signature (HKS) descriptor and the wave kernel signature (WKS) descriptor. At first, we compute the 2D shape distributions of the two kinds of descriptors to represent the 3D model and use them as the input to the networks. Then we construct two convolutional neural networks for the HKS distribution and the WKS distribution separately, and use the multi-feature fusion layer to connect them. The fusion layer not only can exploit more discriminative characteristics of the two descriptors, but also can complement the correlated information between the two kinds of descriptors. Furthermore, to further improve the performance of the description ability, the cross-connected layer is built to combine the low-level features with high-level features. Extensive experiments have validated the effectiveness of the designed multi-feature fusion learning method.

• 한국문헌정보학회지
• /
• 제35권4호
• /
• pp.97-122
• /
• 2001

본 연구에서는 레코드필드 선택이 대규모 서지 데이터베이스 탐색시 미치는 검색 성능에 대하여 관찰하였다. 실험의 구성 요소는 크게 (1) 대규모 상업용 데이터베이스 INSPEC. (2) 관련된 레코드들 (target sets이라고 정의함). (3) 4개의 키워드가 한 세트로 이루어진 4개의 서로 다른 형태의 질의어들 (CT_TF, CT_IDF, UT_TF, UT_IDF), (4) 최적의 질의를 위한 알고리즘, (5) 가능한 모든 경우의 탐색식을 생성해내는 블리언 탐색식 생성기, 그리고 (6) 실제 운영중인 웹 기반의 검색 시스템으로 이뤄졌다. 실험에서의 레코드 필드 선택은 (1) Abstract, (2) Descriptors, (3) Identifiers, (4) 'Subject'(Descriptors + Identifiers). (5) Title. (6) 'All fields'로 정의하여 독립변수로 채택하였다. 검색 성능은 재현율, 정도율을 모두 반영한 Heine의 D측정에 의하여 평가 되었다. 본 연구에서 얻은 주된 결과로는 (1) 필드선택은 검색성능에 중요한 영향을 미치며, (2) 각 검색 성능에서 보여준 순위는 질의어에 따라 민감한 결과를 보였고 (3) 제목(Title)필드 선택이 D측정에서 최적의 결과를 보였다.

• Bulletin of the Korean Chemical Society
• /
• 제30권11호
• /
• pp.2717-2722
• /
• 2009

The use of the classification and regression tree (CART) methodology was studied in a quantitative structure-activity relationship (QSAR) context on a data set consisting of the binding affinities of 39 imidazobenzodiazepines for the α1 benzodiazepine receptor. The 3-D structures of these compounds were optimized using HyperChem software with semiempirical AM1 optimization method. After optimization a set of 1481 zero-to three-dimentional descriptors was calculated for each molecule in the data set. The response (dependent variable) in the tree model consisted of the binding affinities of drugs. Three descriptors (two topological and one 3D-Morse descriptors) were applied in the final tree structure to describe the binding affinities. The mean relative error percent for the data set is 3.20%, compared with a previous model with mean relative error percent of 6.63%. To evaluate the predictive power of CART cross validation method was also performed.

• Genomics & Informatics
• /
• 제7권4호
• /
• pp.212-216
• /
• 2009

WebChemDB is an integrated chemical database retrieval system that provides access to over 8 million publicly available chemical structures, including related information on their biological activities and direct links to other public chemical resources, such as PubChem, ChEBI, and DrugBank. The data are publicly available over the web, using two-dimensional (2D) and three-dimensional (3D) structure retrieval systems with various filters and molecular descriptors. The web services API also provides researchers with functionalities to programmatically manipulate, search, and analyze the data.

• 한국HCI학회:학술대회논문집
• /
• 한국HCI학회 2009년도 학술대회
• /
• pp.669-672
• /
• 2009

제안된 방법은 3차원 모델로부터 형상 기술자를 추출하고, 형상의 유사성을 비교하기 위해 특징 기술자를 이용한다. 대부분의 검색 방법들은 데이터베이스에서 개별적인 3차원 모델의 비교와 검색에 중점이 되어있지만, 본 유사성 검색 방법은 형상 유사성을 이용하여 3차원 물체의 부재 비교와 검색에 초점이 맞추었다. 물체의 부재 유사성 검색 방법은 3차원 모델들의 유사한 부분을 찾는 것과 유사한 부분을 포함하는 3차원 모델을 찾는 것으로 확장된다. 성능 평가를 위한 실험에서 유사한 3차원 석탑 모델의 부재를 효과적으로 검색하였다.