Automatic Extraction of Analytical Chemical Information. System Description, Inventory of Tasks and Problems, and Preliminary Results

Postma, G.J.; Bakel, B.J. van; Kateman, G.

doi:10.1021/ci950206x

Cited by 4 publications

(2 citation statements)

References 32 publications

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“…131 Text mining techniques have advanced since Postma et al reported their system for the semiautomatic extraction of information from abstracts describing analytical methods. 132 They describe the stages of their text analysis in some detail but conclude that their information extraction task is still a time consuming one.…”

Section: Capturing Metadatamentioning

confidence: 99%

Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences

Bird

Frey

2013

Chem. Soc. Rev.

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Recently, a number of organisations have called for open access to scientific information and especially to the data obtained from publicly funded research, among which the Royal Society report and the European Commission press release are particularly notable. It has long been accepted that building research on the foundations laid by other scientists is both effective and efficient. Regrettably, some disciplines, chemistry being one, have been slow to recognise the value of sharing and have thus been reluctant to curate their data and information in preparation for exchanging it. The very significant increases in both the volume and the complexity of the datasets produced has encouraged the expansion of e-Research, and stimulated the development of methodologies for managing, organising, and analysing "big data". We review the evolution of cheminformatics, the amalgam of chemistry, computer science, and information technology, and assess the wider e-Science and e-Research perspective. Chemical information does matter, as do matters of communicating data and collaborating with data. For chemistry, unique identifiers, structure representations, and property descriptors are essential to the activities of sharing and exchange. Open science entails the sharing of more than mere facts: for example, the publication of negative outcomes can facilitate better understanding of which synthetic routes to choose, an aspiration of the Dial-a-Molecule Grand Challenge. The protagonists of open notebook science go even further and exchange their thoughts and plans. We consider the concepts of preservation, curation, provenance, discovery, and access in the context of the research lifecycle, and then focus on the role of metadata, particularly the ontologies on which the emerging chemical Semantic Web will depend. Among our conclusions, we present our choice of the "grand challenges" for the preservation and sharing of chemical information.

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Section: Capturing Metadatamentioning

confidence: 99%

Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences

Bird

Frey

2013

Chem. Soc. Rev.

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“…This study therefore highlights the need for development of standards required for submitting the supporting materials with molecular data in a consistent, truly computable and re-usable format to journals publishing computational research. A specific set of guidelines defined by the publishers to submit molecular data even in a PDF format, would accelerate the automatic processing and recognition of chemical data for further computational studies related to reaction modeling [1–3], drug-discovery [4–7] and molecular inventory management [8, 9]. Several standard molecular representations in ASCII format which are easily readable by molecular modeling and chemoinformatics software packages are available.…”

Section: Introductionmentioning

confidence: 99%

ChemEngine: harvesting 3D chemical structures of supplementary data from PDF files

Karthikeyan

Vyas

2016

J Cheminform

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Digital access to chemical journals resulted in a vast array of molecular information that is now available in the supplementary material files in PDF format. However, extracting this molecular information, generally from a PDF document format is a daunting task. Here we present an approach to harvest 3D molecular data from the supporting information of scientific research articles that are normally available from publisher’s resources. In order to demonstrate the feasibility of extracting truly computable molecules from PDF file formats in a fast and efficient manner, we have developed a Java based application, namely ChemEngine. This program recognizes textual patterns from the supplementary data and generates standard molecular structure data (bond matrix, atomic coordinates) that can be subjected to a multitude of computational processes automatically. The methodology has been demonstrated via several case studies on different formats of coordinates data stored in supplementary information files, wherein ChemEngine selectively harvested the atomic coordinates and interpreted them as molecules with high accuracy. The reusability of extracted molecular coordinate data was demonstrated by computing Single Point Energies that were in close agreement with the original computed data provided with the articles. It is envisaged that the methodology will enable large scale conversion of molecular information from supplementary files available in the PDF format into a collection of ready- to- compute molecular data to create an automated workflow for advanced computational processes. Software along with source codes and instructions available at https://sourceforge.net/projects/chemengine/files/?source=navbar.Graphical abstract. Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-016-0175-x) contains supplementary material, which is available to authorized users.

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Challenges for chemical information extraction and text retrieval

Bakel

Postma

1997

TrAC Trends in Analytical Chemistry

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Automatic Extraction of Analytical Chemical Information. System Description, Inventory of Tasks and Problems, and Preliminary Results

Cited by 4 publications

References 32 publications

Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences

Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences

ChemEngine: harvesting 3D chemical structures of supplementary data from PDF files

Challenges for chemical information extraction and text retrieval

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