Plant Reactome and PubChem: The Plant Pathway and (Bio)Chemical Entity Knowledgebases

Author(s):  
Parul Gupta ◽  
Sushma Naithani ◽  
Justin Preece ◽  
Sunghwan Kim ◽  
Tiejun Cheng ◽  
...  
Keyword(s):  
Molecules ◽  
2021 ◽  
Vol 26 (14) ◽  
pp. 4205
Author(s):  
Dorota Krasowska ◽  
Rafał Karpowicz ◽  
Józef Drabowicz

The purpose of this mini-review is to comprehensively present the synthetic approaches used for the preparation of non-racemic mono- and multi-substituted thiophenes, which, in turn, can be applied as precursors for the synthesis of chiral polythiophenes isolated as a single chemical entity or having supramolecular thin-layer architectures.


2005 ◽  
Vol 528 (1-3) ◽  
pp. 176-182 ◽  
Author(s):  
Kiyotoshi Mori ◽  
Kotaro Takasaki ◽  
Yoshimitsu Katoh ◽  
Hiroshi Yano ◽  
Kimihisa Ueno ◽  
...  

2018 ◽  
Vol 64 ◽  
pp. 86-100 ◽  
Author(s):  
Sara Cheleschi ◽  
Valentina Calamia ◽  
Mercedes Fernandez-Moreno ◽  
Mariangela Biava ◽  
Antonio Giordani ◽  
...  

2016 ◽  
Vol 12 (4) ◽  
pp. 21-44 ◽  
Author(s):  
R. Hema ◽  
T. V. Geetha

The two main challenges in chemical entity recognition are: (i) New chemical compounds are constantly being synthesized infinitely. (ii) High ambiguity in chemical representation in which a chemical entity is being described by different nomenclatures. Therefore, the identification and maintenance of chemical terminologies is a tough task. Since most of the existing text mining methods followed the term-based approaches, the problems of polysemy and synonymy came into the picture. So, a Named Entity Recognition (NER) system based on pattern matching in chemical domain is developed to extract the chemical entities from chemical documents. The Tf-idf and PMI association measures are used to filter out the non-chemical terms. The F-score of 92.19% is achieved for chemical NER. This proposed method is compared with the baseline method and other existing approaches. As the final step, the filtered chemical entities are classified into sixteen functional groups. The classification is done using SVM One against All multiclass classification approach and achieved the accuracy of 87%. One-way ANOVA is used to test the quality of pattern matching method with the other existing chemical NER methods.


2003 ◽  
Vol 45 (3) ◽  
pp. 1-16 ◽  
Author(s):  
Allan Bowditch ◽  
Gustavo Gurrieri ◽  
Beverley Henry

Within the pharmaceutical prescription sector, just like many other markets, maintaining competitive advantage has become increasingly difficult. In the healthcare arena, the period of time that a new chemical entity has on the market before a key competitor emerges has been significantly reduced. If a company has already developed an important market franchise in a given sector or disease area, it is essential that that company understands the potential threats it is likely to face in the future from new product entries and also to appreciate what, if anything, could be done to protect or enhance the product franchise in the light of market developments.


Nature ◽  
1955 ◽  
Vol 176 (4494) ◽  
pp. 1139-1144 ◽  
Author(s):  
C. D. DARLINGTON

2016 ◽  
Author(s):  
Derek R. Buckle ◽  
Paul W. Erhardt ◽  
C. Robin Ganellin ◽  
Toshi Kobayashi ◽  
Thomas J. Perun ◽  
...  

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