DES-ncRNA: A knowledgebase for exploring information about human micro and long noncoding RNAs based on literature-mining

Abstract

Noncoding RNAs (ncRNAs), particularly microRNAs (miRNAs) and long ncRNAs (lncRNAs), are important players in diseases and emerge as novel drug targets. Thus, unraveling the relationships between ncRNAs and other biomedical entities in cells are critical for better understanding ncRNA roles that may eventually help develop their use in medicine. To support ncRNA research and facilitate retrieval of relevant information regarding miRNAs and lncRNAs from the plethora of published ncRNA-related research, we developed DES-ncRNA (www.cbrc.kaust.edu.sa/des_ncrna). DES-ncRNA is a knowledgebase containing text- and data-mined information from public scientific literature and other public resources. Exploration of mined information is enabled through terms and pairs of terms from 19 topic-specific dictionaries including, for example, antibiotics, toxins, drugs, enzymes, mutations, pathways, human genes and proteins, drug indications and side effects, mutations, diseases, etc. DES-ncRNA contains approximately 878,000 associations of terms from these dictionaries of which 36,222 (5,373) are with regards to miRNAs (lncRNAs). We provide several ways to explore information regarding ncRNAs to users including controlled generation of association networks as well as hypotheses generation. We show an example how DES-ncRNA can aid research on Alzheimer disease and suggest potential therapeutic role for Fasudil. DES-ncRNA is a powerful tool that can be used on its own or as a complement to the existing resources, to support research in human ncRNA. To our knowledge, this is the only knowledgebase dedicated to human miRNAs and lncRNAs derived primarily through literature-mining enabling exploration of a broad spectrum of associated biomedical entities, not paralleled by any other resource.

DES-ROD: Exploring Literature to Develop New Links between RNA Oxidation and Human Diseases

“…DES is a text mining and data mining system that allows the exploration of text through enriched concepts and enriched pairs of concepts in topic-specific literature. We used the DES framework to create several topic-specific KBs [32,33,54,67,[69][70][71][72][73][74][75][76][77][78][79][80][81][82]. The underlying systems, workflow, and concept enrichment process used in the current version of DES have been described in [69].…”

Redox control of vascular biology

“…Data-mining and text-mining techniques have been used to explore the information contained in published biomedical literature. Advancements in these techniques have led to the development of several topic-specific knowledgebases (KB), [141][142][143][144][145][146][147][148][149][150][151][152][153][154][155][156][157][158][159] including the first topic-specific KB for redox control of vascular systems, named DES-RedoxVasc. 160 DES-RedoxVasc was constructed using the search query: (human OR mouse OR rat OR mammal*) AND (radical* OR peroxide* OR "reductive stress" OR ROS OR "reactive oxygen species" OR RNS OR "reactive nitrogen species" OR redox OR "reduction-oxidation reaction" OR oxidative OR nitrosative OR peroxide* OR superoxide* OR detoxifi* OR antioxid* OR "polyunsaturated fatty acids" OR "arachidonic acid" OR "linoleic acid" OR hydroperoxide* OR "hypochlorous acid" OR peroxynitrit* flavoprot* OR xanthine oxidase* OR "cytochromes P450" OR catalase* OR sulfiredoxin* OR peroxiredoxin*) AND ("angina pectoris" OR anemia OR aneurysm* OR angio* OR arter* OR atrial OR atrioventricular OR aort* OR bradycardia OR blood OR brain OR circulati* OR clogging OR cardio* OR coronary OR edema OR heart OR ischemic OR hemo* OR hypertension OR leukemia OR leuko* OR macroangiopathy OR microangiopathy OR neovascularization OR occlusion OR pericardi* OR sepsis OR "sickle cell" OR tachycardia OR tachyarrhythmia OR thromb* OR vaso OR vein* OR ventricular OR vascular* OR vessel*) to retrieve all literature specifically focused on research related to redox effects on the cardiovascular system in mammalian organisms.…”

Characterization and identification of long non-coding RNAs based on feature relationship

“…Protein-coding RNAs for human and mouse are both collected from NCBI RefSeq (36) and their corresponding lncRNAs are obtained from Gencode version 22 (37) and Gencode version M7 (38), respectively. For the 12 remaining organisms, both protein-coding RNAs and ncRNAs are downloaded from Ensembl (39). To obtain lncRNAs, ncRNAs shorter than 200nt are excluded.…”

“…Long non-coding RNAs (lncRNAs) are prevalently expressed in a large number of organisms (1)(2)(3)(4)(5). Evidence has accumulated that lncRNAs play vital roles in biological processes including transcriptional regulation, post-transcriptional interference, translational control (6)(7)(8)(9) and are implicated in the development of a variety of human diseases (10)(11)(12)(13)(14). Although the rapid advancement in DNA sequencing technologies has led to an exponential increase in the number of lncRNAs (11,15,16), lncRNAs are often tissue/cell-specific (13,17,18) and lineage/species-specific (18,19) and thus a large number of novel lncRNAs are yet to be discovered.…”