• 제목/요약/키워드: molecular data

검색결과 3,204건 처리시간 0.033초

NMR Data of Flavone Derivatives and Their Anti-oxidative Activities

  • Park, Yeong-Hui;Lee, Yong-Uk;Kim, Ho-Jung;Lee, Young-Shim;Yoon, Young-Ah;Mun, Byeong-Ho;Jeong, Yu-Hun;An, Jung-Hun;Shim, Yhong-Hee;Lim, Yoong-Ho
    • Bulletin of the Korean Chemical Society
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    • 제27권10호
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    • pp.1537-1541
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    • 2006
  • The $^1H$ and $^{13}C$ chemical shifts of eleven flavone derivatives were completely determined by basic 1D and 2D NMR experiments. Nineteen flavone derivatives including the above eleven derivatives were examined for anti-oxidative effects using the 1,1-diphenyl-2-picryl-hydrazyl assay and Caenorhabditis elegans. In order to understand the relationships between the structures of flavone derivatives and their anti-oxidative activities, a Comparative Molecular Field Analysis was performed.

Molecular Design of New Organic Electroluminescence Materials: DCM Derivatives

  • Seong, See-Yearl;Park, Sung-Soo;Seo, Jeong-In;No, Kyoung-Tai;Hong, Jong-In;Park, Su-Jin;Choi, Seung-Hoon;Lee, Han-Yong
    • 한국정보디스플레이학회:학술대회논문집
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    • 한국정보디스플레이학회 2003년도 International Meeting on Information Display
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    • pp.178-180
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    • 2003
  • We performed semiempirical (AMl and ZINDO) and ab initio (HF and DFT) calculations, to investigate molecular structures and optical properties of DCM and its derivatives. DCM and its derivatives are used as a red fluorescent dopant of the organic electroluminescent host materials, $Alq_3$. We have studied the relationship between the molecular structure and the optical properties of these molecules for the improvement of EL efficiencies. Wavelength at the absorption maximum was found to be red-shifted when the molecule is substituted with both strong electron donating and withdrawing functional groups. A new red fluorescent dye was predicted by QSPR study based on calculations and experimental data.

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Pre- and Post-Treatment Imaging of Primary Central Nervous System Tumors in the Molecular and Genetic Era

  • Sung Soo Ahn;Soonmee Cha
    • Korean Journal of Radiology
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    • 제22권11호
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    • pp.1858-1874
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    • 2021
  • Recent advances in the molecular and genetic characterization of central nervous system (CNS) tumors have ushered in a new era of tumor classification, diagnosis, and prognostic assessment. In this emerging and rapidly evolving molecular genetic era, imaging plays a critical role in the preoperative diagnosis and surgical planning, molecular marker prediction, targeted treatment planning, and post-therapy assessment of CNS tumors. This review provides an overview of the current imaging methods relevant to the molecular genetic classification of CNS tumors. Specifically, we focused on 1) the correlates between imaging features and specific molecular genetic markers and 2) the post-therapy imaging used for therapeutic assessment.

Atomic and Molecular Data Research for Plasma Applications

  • 윤정식;권득철;송미영;장원석;황성하;박준형
    • 한국진공학회:학술대회논문집
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    • 한국진공학회 2010년도 제39회 하계학술대회 초록집
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    • pp.32-32
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    • 2010
  • Since the characteristics of plasmas depend strongly on the interactions between plasma particles such as electron, ions, and neutrals, a well-established atomic and molecular database is needed to understand and produce various types of plasma. Thus, National Fusion Research Institute (NFRI) started to establish the plasma property DB for fusion and industrial plasma from last 2002. Here we describe our recent data evaluation activities regarding to production of atomic and molecular data that are needed for modeling plasma in fusion tokamaks and also low temperature industrial plasmas.

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Identification of ERBB pathway-activated cells in triple-negative breast cancer

  • Cho, Soo Young
    • Genomics & Informatics
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    • 제17권1호
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    • pp.3.1-3.4
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    • 2019
  • Intratumor heterogeneity within a single tumor mass is one of the hallmarks of malignancy and has been reported in various tumor types. The molecular characterization of intratumor heterogeneity in breast cancer is a significant challenge for effective treatment. Using single-cell RNA sequencing (RNA-seq) data from a public resource, an ERBB pathway activated triple-negative cell population was identified. The differential expression of three subtyping marker genes (ERBB2, ESR1, and PGR) was not changed in the bulk RNA-seq data, but the single-cell transcriptomes showed intratumor heterogeneity. This result shows that ERBB signaling is activated using an indirect route and that the molecular subtype is changed on a single-cell level. Our data propose a different view on breast cancer subtypes, clarifying much confusion in this field and contributing to precision medicine.

Clinical, Histopathological and Molecular Characteristics of Metastatic Breast Cancer in North-Eastern Kazakhstan: a 10 Year Retrospective Study

  • Abiltayeva, Aizhan;Moore, Malcolm A;Myssayev, Ayan;Adylkhanov, Tasbolat;Baissalbayeva, Ainur;Zhabagin, Kuantkan;Beysebayev, Eldar
    • Asian Pacific Journal of Cancer Prevention
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    • 제17권10호
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    • pp.4797-4802
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    • 2016
  • Background: Breast cancer (BC) is the top cancer among women worldwide and has been the most frequent malignancy among Kazakhstan women over the past few decades. Information on clinical and histopathological features of metastatic breast cancer (MBC), as well as the distribution of molecular subtypes is limited for Kazakh people. Materials and Methods: The present observational retrospective study was carried out at Regional Oncologic Dispensaries in the North-East Region of Kazakhstan (in Semey and Pavlodar cities). Сlinical and histopathological data were obtained for a total of 570 MBC patients in the 10 year period from 2004-2013, for whom data on molecular subtype were available for 253. Data from hospital charts were entered into SPSS 20 for analysis by one-way ANOVA analysis of associations of different variables with 1-5 year survival. Pearson correlation and linear regression models were used to examine the relation between parameters with a p-value < 0.05 considered statistically significant. Results: No significant relationships were evident between molecular subtype and survival, site of metastases, stage or ethnicity. Young females below the age of 44 were slightly more likely to have triple negative lesions. While the ductal type greatly predomonated, luminal A and B cases had a higher percentage with lobular morphology. Conclusions: In this select group of metastatice brease cancer, no links were noted for survival with molecular subtype, in contrast to much of the literature.

당뇨병 치료제 후보약물 정보를 이용한 기계 학습 모델과 주요 분자표현자 도출 (A machine learning model for the derivation of major molecular descriptor using candidate drug information of diabetes treatment)

  • 남궁윤;김창욱;이창준
    • 한국융합학회논문지
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    • 제10권3호
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    • pp.23-30
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    • 2019
  • 본 연구는 당뇨병 치료제 후보약물 정보를 이용하여 항당뇨에 영향을 미치는 물질구조를 발견하는데 목적이 있다. 정량적구조 활성관계를 이용한 기계 학습 모델을 만들고 부분최소자승 알고리즘을 통해 실험데이터 별로 결정계수를 파악한 후 변수중요도척도를 활용하여 주요 분자표현자를 도출하였다. 연구 결과, 후보약물 구조정보를 반영한 molecular access system fingerprint 데이터로 분석한 결과가 in vitro 데이터를 이용한 분석 결과보다 설명력이 높았으며, 항당뇨에 영향을 미치는 주요 분자표현자 역시 다양하게 도출할 수 있었다. 제안된 항당뇨 예측 및 주요인자 분석 방법을 활용한다면 유사한 과정을 반복 실험하는 기존 신약개발 방식과는 달리, 많은 비용과 시간이 소요되는 후보물질 스크리닝 (screening) 기간을 최소화하고, 신약개발 탐색기간도 단축하는 계기가 될 수 있을 것으로 기대한다.

DNA Fingerprinting of Jute Germplasm by RAPD

  • Hossain, Mohammad Belayat;Haque, Samiul;Khan, Haseena
    • BMB Reports
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    • 제35권4호
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    • pp.414-419
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    • 2002
  • The genotype characteristic of cultivars was investigated, along with varieties of both of the jute species, Corchorus olitorius and Corchorus capsularis, in the germplasm collection at the Bangladesh Jute Research Institute (BJRI). DNA fingerprinting was generated for 9 different varieties and 12 accessions of jute cultivars by using random amplified polymorphic DNA(RAPD). A total of 29 arbitrary oligonucleotide primers were screened. Seven primers gave polymorphism within the varieties, and 6 primers detected polymorphism within the accessions that were tested. A dendrogram was engendered from these data, and this gave a distinct clustering of the cultivated species of jute. Therefore, we generated RAPD markers, which are species-specific. These primers can distinguish between C. olitorius and C. capsularis. From the dendrogram that we generated between the various members of these two species, we found the existing genetic classification that agrees with our molecular marking data. A different dendrogram showed that jute accessions could be clustered into three groups. These data will be invaluable in the conservation and utilization of the genetic pool in the germplasm collection.

분자구조 유사도를 활용한 약물 효능 예측 알고리즘 연구 (A Study on the Prediction of Drug Efficacy by Using Molecular Structure)

  • 정화영;송창현;조혜연;기재홍
    • 대한의용생체공학회:의공학회지
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    • 제43권4호
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    • pp.230-240
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    • 2022
  • Drug regeneration technology is an efficient strategy than the existing new drug development process, which requires large costs and time by using drugs that have already been proven safe. In this study, we recognize the importance of the new drug regeneration aspect of new drug development and research in predicting functional similarities through the basic molecular structure that forms drugs. We test four string-based algorithms by using SMILES data and searching for their similarities. And by using the ATC codes, pair them with functional similarities, which we compare and validate to select the optimal model. We confirmed that the higher the molecular structure similarity, the higher the ATC code matching rate. We suggest the possibility of additional potency of random drugs, which can be predicted through data that give information on drugs with high molecular similarities. This model has the advantage of being a great combination with additional data, so we look forward to using this model in future research.

3D 프린팅 소재 화학물질의 독성 예측을 위한 Data-centric XAI 기반 분자 구조 Data Imputation과 QSAR 모델 개발 (Data-centric XAI-driven Data Imputation of Molecular Structure and QSAR Model for Toxicity Prediction of 3D Printing Chemicals)

  • 정찬혁;김상윤;허성구;;신민혁;유창규
    • Korean Chemical Engineering Research
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    • 제61권4호
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    • pp.523-541
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    • 2023
  • 3D 프린터의 활용이 높아짐에 따라 발생하는 화학물질에 대한 노출 빈도가 증가하고 있다. 그러나 3D 프린팅 발생 화학물질의 독성 및 유해성에 대한 연구는 미비하며, 분자 구조 데이터의 결측치로 인해 in silico 기법을 사용한 독성예측 연구는 저조한 실정이다. 본 연구에서는 화학물질의 분자구조 정보를 나타내는 주요 분자표현자의 결측치를 보간하여 3D 프린팅의 독성 및 유해성을 예측한 Data-centric QSAR 모델을 개발하였다. 먼저 MissForest 알고리즘을 사용해 3D 프린팅으로 발생되는 유해물질의 분자표현자 결측치를 보완하였으며, 서로 다른 4가지 기계학습 모델(결정트리, 랜덤포레스트, XGBoost, SVM)을 기반으로 Data-centric QSAR 모델을 개발하여 생물 농축 계수(Log BCF)와 옥탄올-공기분배계수(Log Koa), 분배계수(Log P)를 예측하였다. 또한, 설명 가능한 인공지능(XAI) 방법론 중 TreeSHAP (SHapley Additive exPlanations) 기법을 활용하여 Data-centric QSAR 모델의 신뢰성을 입증하였다. MissForest 알고리즘 기반 결측지 보간 기법은, 기존 분자구조 데이터에 비하여 약 2.5배 많은 분자구조 데이터를 확보할 수 있었다. 이를 바탕으로 개발된 Data-centric QSAR 모델의 성능은 Log BCF, Log Koa와 Log P를 각각 73%, 76%, 92% 의 예측 성능으로 예측할 수 있었다. 마지막으로 Tree-SHAP 분석결과 개발된 Data-centric QSAR 모델은 각 독성치와 물리적으로 상관성이 높은 분자표현자를 통하여 선택함을 설명할 수 있었고 독성 정보에 대한 높은 예측 성능을 확보할 수 있었다. 본 연구에서 개발한 방법론은 다른 프린팅 소재나 화학공정, 그리고 반도체/디스플레이 공정에서 발생 가능한 오염물질의 독성 및 인체 위해성 평가에 활용될 수 있을 것으로 사료된다.