• 제목/요약/키워드: 2D Descriptors

검색결과 50건 처리시간 0.02초

Prediction Models of P-Glycoprotein Substrates Using Simple 2D and 3D Descriptors by a Recursive Partitioning Approach

  • Joung, Jong-Young;Kim, Hyoung-Joon;Kim, Hwan-Mook;Ahn, Soon-Kil;Nam, Ky-Youb;No, Kyoung-Tai
    • Bulletin of the Korean Chemical Society
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    • 제33권4호
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    • pp.1123-1127
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    • 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.

Three-Dimensional Shape Recognition and Classification Using Local Features of Model Views and Sparse Representation of Shape Descriptors

  • Kanaan, Hussein;Behrad, Alireza
    • Journal of Information Processing Systems
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    • 제16권2호
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    • pp.343-359
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    • 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.

Safety assessment of biological nanofood products via intelligent computer simulation

  • Zhao, Yunfeng;Zhang, Le
    • Advances in nano research
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    • 제13권2호
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    • pp.121-134
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    • 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.

Exploring Level Descriptors of Geometrical Thinking

  • Srichompoo, Somkuan;Inprasitha, Maitree;Sangaroon, Kiat
    • 한국수학교육학회지시리즈D:수학교육연구
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    • 제15권1호
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    • pp.81-91
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    • 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.

서지 데이터베이스에서의 레코드 필드 선택이 검색 성능에 미치는 영향에 관한 연구 (A Study of the Influence of Choice of Record Fields on Retrieval Performance in the Bibliographic Database)

  • Heesop Kim
    • 한국문헌정보학회지
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    • 제35권4호
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    • pp.97-122
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    • 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.

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WebChemDB: An Integrated Chemical Database Retrieval System

  • Hou, Bo-Kyeng;Moon, Eun-Joung;Moon, Sung-Chul;Kim, Hae-Jin
    • Genomics & Informatics
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    • 제7권4호
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    • pp.212-216
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    • 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.

Convolutional Neural Network Based Multi-feature Fusion for Non-rigid 3D Model Retrieval

  • Zeng, Hui;Liu, Yanrong;Li, Siqi;Che, JianYong;Wang, Xiuqing
    • Journal of Information Processing Systems
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    • 제14권1호
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    • pp.176-190
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    • 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.

Human Action Recognition Via Multi-modality Information

  • Gao, Zan;Song, Jian-Ming;Zhang, Hua;Liu, An-An;Xue, Yan-Bing;Xu, Guang-Ping
    • Journal of Electrical Engineering and Technology
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    • 제9권2호
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    • pp.739-748
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    • 2014
  • In this paper, we propose pyramid appearance and global structure action descriptors on both RGB and depth motion history images and a model-free method for human action recognition. In proposed algorithm, we firstly construct motion history image for both RGB and depth channels, at the same time, depth information is employed to filter RGB information, after that, different action descriptors are extracted from depth and RGB MHIs to represent these actions, and then multimodality information collaborative representation and recognition model, in which multi-modality information are put into object function naturally, and information fusion and action recognition also be done together, is proposed to classify human actions. To demonstrate the superiority of the proposed method, we evaluate it on MSR Action3D and DHA datasets, the well-known dataset for human action recognition. Large scale experiment shows our descriptors are robust, stable and efficient, when comparing with the-state-of-the-art algorithms, the performances of our descriptors are better than that of them, further, the performance of combined descriptors is much better than just using sole descriptor. What is more, our proposed model outperforms the state-of-the-art methods on both MSR Action3D and DHA datasets.

Classification of Piperazinylalkylisoxazole Library by Recursive Partitioning

  • Kim, Hye-Jung;Park, Woo-Kyu;Cho, Yong-Seo;No, Kyoung-Tai;Koh, Hun-Yeong;Choo, Hyun-Ah;Pae, Ae-Nim
    • Bulletin of the Korean Chemical Society
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    • 제29권1호
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    • pp.111-116
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    • 2008
  • A piperazinylalkylisoxazole library containing 86 compounds was constructed and evaluated for the binding affinities to dopamine (D3) and serotonin (5-HT2A/2C) receptor to develop antipsychotics. Dopamine antagonists (DA) showing selectivity for D3 receptor over the D2 receptor, serotonin antagonists (SA), and serotonin-dopamine dual antagonists (SDA) were identified based on their binding affinity and selectivity. The analogues were divided into three groups of 7 DAs (D3), 33 SAs (5-HT2A/2C), and 46 SDAs (D3 and 5-HT2A/2C). A classification model was generated for identifying structural characteristics of those antagonists with different affinity profiles. On the basis of the results from our previous study, we conducted the generation of the decision trees by the recursive-partitioning (RP) method using Cerius2 2D descriptors, and identified and interpreted the descriptors that discriminate in-house antipsychotic compounds.

다중 곡률-단계 공간 기술자를 이용한 다중형상 검색 (Multi-Shape Retrieval Using Multi Curvature-Scale Space Descriptor)

  • 박상현;이수찬;윤일동
    • 방송공학회논문지
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    • 제13권6호
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    • pp.962-965
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    • 2008
  • 2차원 형상기술자는 형상의 특성을 수치화하여 형상의 분류와 비교를 가능하게 하며, 영상 검색 및 3차원 모델 검색 등에 적용되어왔다. 기존에 개발된 기술자들은 한 형상의 외곽선에 해당하는 폐곡선만을 기술하거나 정밀성이 떨어진다는 한계가 있었다. 이에 따라 본 논문에서는 하나 이상의 폐곡선으로 이루어진 다중형상에 적용하기 위한 다중 곡률-단계 공간 (Multi Curvature-Scale Space) 기술자를 제안한다. 구체적으로, 하나의 폐곡선을 기술하는데 뛰어난 곡률-단계공간 기술자를 각 폐곡선에 적용하고, 이와 함께 전체 형상내의 각 폐곡선들의 배치 형태를 수치화하여 전체 형상을 기술한다. 또한, 기술자를 구성하는 각 값의 가중치를 조절할 수 있게 하여 사용자에 따른 유사도의 모호함을 극복할 수 있게 하였다. 제시하는 다양한 실험 결과는 제안하는 기술자의 유용함을 나타낸다.