Mubarak Himmat

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Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological(More)
One of the most widely-used techniques for ligand-based virtual screening is similarity searching. This study adopted the concepts of quantum mechanics to present as state-of-the-art similarity method of molecules inspired from quantum theory. The representation of molecular compounds in mathematical quantum space plays a vital role in the development of(More)
Chemical documents, especially those involving drug information, comprise a variety of types – the most common being journal articles, patents and theses. They typically contain large amounts of chemical information, such as PubMed-ID, activity classes and adverse or side effects. Techniques are used to extract information from a huge number of documents(More)
Quantifying the similarity of molecules is considered one of the major tasks in virtual screening. There are many similarity measures that have been proposed for this purpose, some of which have been derived from document and text retrieving areas as most often these similarity methods give good results in document retrieval and can achieve good results in(More)
Computational methods in drug discovery have increasingly gained attention of researchers within the last decades, as the tools for facilitating drug discovery process, for it allow rapid screening of huge databases , the ligand-abased virtual screening (LBVS) methods continue to be developed and improved as one of the important tool of drug discovery(More)
The volume of electronic documents has rapidly increased and the scientific literature has increased too. These huge documents contain considerable information, but it has to be retrieved and managed in a constructive and useful way. Information Extraction (IE) is the field of extracting useful information using different methods and approaches by means of(More)
Extraction of drug-adverse effect causal relationship supports pharmacovigilance research and reduces the manual efforts for some tasks such as drug safety monitoring and building databases for adverse drugs effects from free text. In this study, we proposed a pattern-based method to extract drug-adverse effects causal relation from medical case reports and(More)
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