Systematic Drug Repurposing Through Text Mining
Drug development remains a time-consuming and highly expensive process with high attrition rates at each stage. Given the safety hurdles drugs must pass due to increased regulatory scrutiny, it is essential for pharmaceutical companies to maximize their return on investment by effectively extending drug life cycles. There have been many effective techniques, such as phenotypic screening and compound profiling, which identify new indications for existing drugs, often referred to as drug repurposing or drug repositioning. This chapter explores the use of text mining leveraging several publicly available knowledge resources a...
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Role of Text Mining in Early Identification of Potential Drug Safety Issues
Drugs are an important part of today’s medicine, designed to treat, control, and prevent diseases; however, besides their therapeutic effects, drugs may also cause adverse effects that range from cosmetic to severe morbidity and mortality. To identify these potential drug safety issues early, surveillance must be conducted for each drug throughout its life cycle, from drug development to different phases of clinical trials, and continued after market approval. A major aim of pharmacovigilance is to identify the potential drug–event associations that may be novel in nature, severity, and/or frequency. Currently,...
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Integrative Literature and Data Mining to Rank Disease Candidate Genes
While the genomics-derived discoveries promise benefits to basic research and health care, the speed and affordability of sequencing following recent technological advances has further aggravated the data deluge. Seamless integration of the ever-increasing clinical, genomic, and experimental data and efficient mining for knowledge extraction, delivering actionable insight and generating testable hypotheses are therefore critical for the needs of biomedical research. For instance, high-throughput techniques are frequently applied to detect disease candidate genes. Experimental validation of these candidates however is both ...
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Mining Emerging Biomedical Literature for Understanding Disease Associations in Drug Discovery
Systematically evaluating the exponentially growing body of scientific literature has become a critical task that every drug discovery organization must engage in in order to understand emerging trends for scientific investment and strategy development. Developing trends analysis uses the number of publications within a 3-year window to determine concepts derived from well-established disease and gene ontologies to aid in recognizing and predicting emerging areas of scientific discoveries relevant to that space. In this chapter, we describe such a method and use obesity and psoriasis as use-case examples by analyzing the f...
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Scientific Collaboration Networks Using Biomedical Text
The combination of scientific knowledge and experience is the key success for biomedical research. This chapter demonstrates some of the strategies used to help in identifying key opinion leaders with the expertise you need, thus enabling an effort to increase collaborative biomedical research. (Source: Springer protocols feed by Bioinformatics)
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Mining Biological Networks from Full-Text Articles
The study of biological networks is playing an increasingly important role in the life sciences. Many different kinds of biological system can be modelled as networks; perhaps the most important examples are protein–protein interaction (PPI) networks, metabolic pathways, gene regulatory networks, and signalling networks. Although much useful information is easily accessible in publicly databases, a lot of extra relevant data lies scattered in numerous published papers. Hence there is a pressing need for automated text-mining methods capable of extracting such information from full-text articles. Here we present pract...
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Functional Molecular Units for Guiding Biomarker Panel Design
The field of biomarker research has experienced a major boost in recent years, and the number of publications on biomarker studies evaluating given, but also proposing novel biomarker candidates is increasing rapidly for numerous clinically relevant disease areas. However, individual markers often lack sensitivity and specificity in the clinical context, resting essentially on the intra-individual phenotype variability hampering sensitivity, or on assessing more general processes downstream of the causative molecular events characterizing a disease term, in consequence impairing disease specificity. The trend to circumvent...
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Roles for Text Mining in Protein Function Prediction
The Human Genome Project has provided science with a hugely valuable resource: the blueprints for life; the specification of all of the genes that make up a human. While the genes have all been identified and deciphered, it is proteins that are the workhorses of the human body: they are essential to virtually all cell functions and are the primary mechanism through which biological function is carried out. Hence in order to fully understand what happens at a molecular level in biological organisms, and eventually to enable development of treatments for diseases where some aspect of a biological system goes awry, we must un...
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Predicting Future Discoveries from Current Scientific Literature
Knowledge discovery in biomedicine is a time-consuming process starting from the basic research, through preclinical testing, towards possible clinical applications. Crossing of conceptual boundaries is often needed for groundbreaking biomedical research that generates highly inventive discoveries. We demonstrate the ability of a creative literature mining method to advance valuable new discoveries based on rare ideas from existing literature. When emerging ideas from scientific literature are put together as fragments of knowledge in a systematic way, they may lead to original, sometimes surprising, research findings. If ...
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Biological Information Extraction and Co-occurrence Analysis
Nowadays, it is possible to identify terms corresponding to biological entities within passages in biomedical text corpora: critically, their potential relationships then need to be detected. These relationships are typically detected by co-occurrence analysis, revealing associations between bioentities through their coexistence in single sentences and/or entire abstracts. These associations implicitly define networks, whose nodes represent terms/bioentities/concepts being connected by relationship edges; edge weights might represent confidence for these semantic connections. (Source: Springer protocols feed by Bioinformatics)
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Text Mining for Drug–Drug Interaction
In order to understand the mechanisms of drug–drug interaction (DDI), the study of pharmacokinetics (PK), pharmacodynamics (PD), and pharmacogenetics (PG) data are significant. In recent years, drug PK parameters, drug interaction parameters, and PG data have been unevenly collected in different databases and published extensively in literature. Also the lack of an appropriate PK ontology and a well-annotated PK corpus, which provide the background knowledge and the criteria of determining DDI, respectively, lead to the difficulty of developing DDI text mining tools for PK data collection from the literature and data...
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Mapping of Biomedical Text to Concepts of Lexicons, Terminologies, and Ontologies
Concept mapping is a fundamental task in biomedical text mining in which textual mentions of concepts of interest are annotated with specific entries of lexicons, terminologies, ontologies, or databases representing these concepts. Though there has been a significant amount of research, there are still a limited number of practical, publicly available tools for concept mapping of biomedical text specified by the user as an independent task. In this chapter, several tools that can automatically map biomedical text to concepts from a wide range of terminological resources are presented, followed by those that can map to more...
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Accessing Biomedical Literature in the Current Information Landscape
We present this chapter in the light of three consecutive steps of literature access: searching for citations, retrieving full text, and viewing the article. The first section presents the current state of practice of biomedical literature access, including an analysis of the search tools most frequently used by the users, including PubMed, Google Scholar, Web of Science, Scopus, and Embase, and a study on biomedical literature archives such as PubMed Central. The next section describes current research and the state-of-the-art systems motivated by the challenges a user faces during query formulation and interpretation of ...
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Introduction to Biomedical Literature Text Mining: Context and Objectives
Information: If you are reading this, you know how important it is and almost certainly look to the biomedical literature for a large part of the information you need. We work hard to find more and more biomedical literature, seeking new content from multiple sources. But, can there be too much of a good thing? (Source: Springer protocols feed by Bioinformatics)
Source: Springer protocols feed by Bioinformatics - May 2, 2014 Category: Bioinformatics Source Type: news
Computational Prediction of RNA–RNA Interactions
We describe different tools and approaches for RNA–RNA interaction prediction. Recognition of ncRNA targets is predominantly governed by two principles, namely the stability of the duplex between the two interacting RNAs and the internal structure of both mRNA and ncRNA. Thus, approaches can be distinguished into different major categories depending on how they consider inter- and intramolecular structure. The first class completely neglects the internal structure and measures only the stability of the duplex. The second class of approaches abstracts from specific intramolecular structures and uses an ensemble-based ...
Source: Springer protocols feed by Bioinformatics - December 4, 2013 Category: Bioinformatics Source Type: news
