DES-Amyloidoses "Amyloidoses through the looking-glass": A knowledgebase developed for exploring and linking information related to human amyloid-related diseases.

More than 30 types of amyloids are linked to close to 50 diseases in humans, the most prominent being Alzheimer's disease (AD). AD is brain-related local amyloidosis, while another amyloidosis, such as AA amyloidosis, tends to be more systemic. Therefore, we need to know more about the biological entities' influencing these amyloidosis processes. However, there is currently no support system developed specifically to handle this extraordinarily complex and demanding task. To acquire a systematic view of amyloidosis and how this may be relevant to the brain and other organs, we needed a means to explore "amyloid network systems" that may underly processes that leads to an amyloid-related disease. In this regard, we developed the DES-Amyloidoses knowledgebase (KB) to obtain fast and relevant information regarding the biological network related to amyloid proteins/peptides and amyloid-related diseases. This KB contains information obtained through text and data mining of available scientific literature and other public repositories. The information compiled into the DES-Amyloidoses system based on 19 topic-specific dictionaries resulted in 796,409 associations between terms from these dictionaries. Users can explore this information through various options, including enriched concepts, enriched pairs, and semantic similarity. We show the usefulness of the KB using an example focused on inflammasome-amyloid associations. To our knowledge, this is the only KB dedicated to human amyloid-related diseases derived primarily through literature text mining and complemented by data mining that provides a novel way of exploring information relevant to amyloidoses.

Re-infection with a different SARS-CoV-2 clade and prolonged viral shedding in a hematopoietic stem cell transplantation patient.

Immunocompromised patients who have a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection pose many clinical and public health challenges. We describe the case of a hematopoietic stem cell transplantation patient with lymphoma who had a protracted illness requiring three consecutive hospital admissions. Whole genome sequencing confirmed two different SARS-CoV-2 clades. Clinical management issues and the unanswered questions arising from this case are discussed.

IBDDB: a manually curated and text-mining-enhanced database of genes involved in inflammatory bowel disease.

To date, research on inflammatory bowel disease (IBD, encompassing Crohn's disease and ulcerative colitis), a chronic complex disorder, has generated a large amount of data scattered across published literature (1 06 333) listed in PubMed on 14 October 2020, and no dedicated database currently exists that catalogues information on genes associated with IBD. We aimed to manually curate 289 genes that are experimentally validated to be linked with IBD and its known phenotypes. Furthermore, we have developed an integrated platform providing information about different aspects of these genes by incorporating several resources and an extensive text-mined knowledgebase. The curated IBD database (IBDDB) allows the selective display of collated 34 subject-specific concepts (listed as columns) exportable through a user-friendly IBDDB portal. The information embedded in concepts was acquired via text-mining of PubMed (manually cleaned and curated), accompanied by data-mining from varied resources. The user can also explore different biomedical entities and their co-occurrence with other entities (about one million) from 11 curated dictionaries in the indexed PubMed records. This functionality permits the user to generate and cross-examine a new hypothesis that is otherwise not easy to comprehend by just reading the published abstracts and papers. Users can download required information using various file formats and can display information in the form of networks. To our knowledge, no curated database of IBD-related genes is available so far. IBDDB is free for academic users and can be accessed at https://www.cbrc.kaust.edu.sa/ibd/.

DES-Mutation: System for Exploring Links of Mutations and Diseases.

During cellular division DNA replicates and this process is the basis for passing genetic information to the next generation. However, the DNA copy process sometimes produces a copy that is not perfect, that is, one with mutations. The collection of all such mutations in the DNA copy of an organism makes it unique and determines the organism's phenotype. However, mutations are often the cause of diseases. Thus, it is useful to have the capability to explore links between mutations and disease. We approached this problem by analyzing a vast amount of published information linking mutations to disease states. Based on such information, we developed the DES-Mutation knowledgebase which allows for exploration of not only mutation-disease links, but also links between mutations and concepts from 27 topic-specific dictionaries such as human genes/proteins, toxins, pathogens, etc. This allows for a more detailed insight into mutation-disease links and context. On a sample of 600 mutation-disease associations predicted and curated, our system achieves precision of 72.83%. To demonstrate the utility of DES-Mutation, we provide case studies related to known or potentially novel information involving disease mutations. To our knowledge, this is the first mutation-disease knowledgebase dedicated to the exploration of this topic through text-mining and data-mining of different mutation types and their associations with terms from multiple thematic dictionaries.

DES-TOMATO: A Knowledge Exploration System Focused On Tomato Species.

Tomato is the most economically important horticultural crop used as a model to study plant biology and particularly fruit development. Knowledge obtained from tomato research initiated improvements in tomato and, being transferrable to other such economically important crops, has led to a surge of tomato-related research and published literature. We developed DES-TOMATO knowledgebase (KB) for exploration of information related to tomato. Information exploration is enabled through terms from 26 dictionaries and combination of these terms. To illustrate the utility of DES-TOMATO, we provide several examples how one can efficiently use this KB to retrieve known or potentially novel information. DES-TOMATO is free for academic and nonprofit users and can be accessed at http://cbrc.kaust.edu.sa/des_tomato/, using any of the mainstream web browsers, including Firefox, Safari and Chrome.

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

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.

bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli.

Motivation: The computational search for promoters in prokaryotes remains an attractive problem in bioinformatics. Despite the attention it has received for many years, the problem has not been addressed satisfactorily. In any bacterial genome, the transcription start site is chosen mostly by the sigma (σ) factor proteins, which control the gene activation. The majority of published bacterial promoter prediction tools target σ 70 promoters in Escherichia coli . Moreover, no σ-specific classification of promoters is available for prokaryotes other than for E. coli . Results: Here, we introduce bTSSfinder, a novel tool that predicts putative promoters for five classes of σ factors in Cyanobacteria (σ A , σ C , σ H , σ G and σ F ) and for five classes of sigma factors in E. coli (σ 70 , σ 38 , σ 32 , σ 28 and σ 24 ). Comparing to currently available tools, bTSSfinder achieves higher accuracy (MCC = 0.86, F 1 -score = 0.93) compared to the next best tool with MCC = 0.59, F 1 -score = 0.79) and covers multiple classes of promoters. Availability and Implementation: bTSSfinder is available standalone and online at http://www.cbrc.kaust.edu.sa/btssfinder . Contacts: ilham.shahmuradov@kaust.edu.sa or vladimir.bajic@kaust.edu.sa. Supplementary information: Supplementary data are available at Bioinformatics online.

DESM: portal for microbial knowledge exploration systems.

Microorganisms produce an enormous variety of chemical compounds. It is of general interest for microbiology and biotechnology researchers to have means to explore information about molecular and genetic basis of functioning of different microorganisms and their ability for bioproduction. To enable such exploration, we compiled 45 topic-specific knowledgebases (KBs) accessible through DESM portal (www.cbrc.kaust.edu.sa/desm). The KBs contain information derived through text-mining of PubMed information and complemented by information data-mined from various other resources (e.g. ChEBI, Entrez Gene, GO, KOBAS, KEGG, UniPathways, BioGrid). All PubMed records were indexed using 4,538,278 concepts from 29 dictionaries, with 1 638 986 records utilized in KBs. Concepts used are normalized whenever possible. Most of the KBs focus on a particular type of microbial activity, such as production of biocatalysts or nutraceuticals. Others are focused on specific categories of microorganisms, e.g. streptomyces or cyanobacteria. KBs are all structured in a uniform manner and have a standardized user interface. Information exploration is enabled through various searches. Users can explore statistically most significant concepts or pairs of concepts, generate hypotheses, create interactive networks of associated concepts and export results. We believe DESM will be a useful complement to the existing resources to benefit microbiology and biotechnology research.

DENdb: database of integrated human enhancers.

Enhancers are cis-acting DNA regulatory regions that play a key role in distal control of transcriptional activities. Identification of enhancers, coupled with a comprehensive functional analysis of their properties, could improve our understanding of complex gene transcription mechanisms and gene regulation processes in general. We developed DENdb, a centralized on-line repository of predicted enhancers derived from multiple human cell-lines. DENdb integrates enhancers predicted by five different methods generating an enriched catalogue of putative enhancers for each of the analysed cell-lines. DENdb provides information about the overlap of enhancers with DNase I hypersensitive regions, ChIP-seq regions of a number of transcription factors and transcription factor binding motifs, means to explore enhancer interactions with DNA using several chromatin interaction assays and enhancer neighbouring genes. DENdb is designed as a relational database that facilitates fast and efficient searching, browsing and visualization of information. Database URL: http://www.cbrc.kaust.edu.sa/dendb/.

DEOP: a database on osmoprotectants and associated pathways.

Microorganisms are known to counteract salt stress through salt influx or by the accumulation of osmoprotectants (also called compatible solutes). Understanding the pathways that synthesize and/or breakdown these osmoprotectants is of interest to studies of crops halotolerance and to biotechnology applications that use microbes as cell factories for production of biomass or commercial chemicals. To facilitate the exploration of osmoprotectants, we have developed the first online resource, 'Dragon Explorer of Osmoprotection associated Pathways' (DEOP) that gathers and presents curated information about osmoprotectants, complemented by information about reactions and pathways that use or affect them. A combined total of 141 compounds were confirmed osmoprotectants, which were matched to 1883 reactions and 834 pathways. DEOP can also be used to map genes or microbial genomes to potential osmoprotection-associated pathways, and thus link genes and genomes to other associated osmoprotection information. Moreover, DEOP provides a text-mining utility to search deeper into the scientific literature for supporting evidence or for new associations of osmoprotectants to pathways, reactions, enzymes, genes or organisms. Two case studies are provided to demonstrate the usefulness of DEOP. The system can be accessed at. Database URL: http://www.cbrc.kaust.edu.sa/deop/

Exploration of miRNA families for hypotheses generation.

Technological improvements have resulted in increased discovery of new microRNAs (miRNAs) and refinement and enrichment of existing miRNA families. miRNA families are important because they suggest a common sequence or structure configuration in sets of genes that hint to a shared function. Exploratory tools to enhance investigation of characteristics of miRNA families and the functions of family-specific miRNA genes are lacking. We have developed, miRNAVISA, a user-friendly web-based tool that allows customized interrogation and comparisons of miRNA families for hypotheses generation, and comparison of per-species chromosomal distribution of miRNA genes in different families. This study illustrates hypothesis generation using miRNAVISA in seven species. Our results unveil a subclass of miRNAs that may be regulated by genomic imprinting, and also suggest that some miRNA families may be species-specific, as well as chromosome- and/or strand-specific.

Information exploration system for sickle cell disease and repurposing of hydroxyfasudil.

BACKGROUND: Sickle cell disease (SCD) is a fatal monogenic disorder with no effective cure and thus high rates of morbidity and sequelae. Efforts toward discovery of disease modifying drugs and curative strategies can be augmented by leveraging the plethora of information contained in available biomedical literature. To facilitate research in this direction we have developed a resource, Dragon Exploration System for Sickle Cell Disease (DESSCD) (http://cbrc.kaust.edu.sa/desscd/) that aims to promote the easy exploration of SCD-related data. DESCRIPTION: The Dragon Exploration System (DES), developed based on text mining and complemented by data mining, processed 419,612 MEDLINE abstracts retrieved from a PubMed query using SCD-related keywords. The processed SCD-related data has been made available via the DESSCD web query interface that enables: a/information retrieval using specified concepts, keywords and phrases, and b/the generation of inferred association networks and hypotheses. The usefulness of the system is demonstrated by: a/reproducing a known scientific fact, the "Sickle_Cell_Anemia-Hydroxyurea" association, and b/generating novel and plausible "Sickle_Cell_Anemia-Hydroxyfasudil" hypothesis. A PCT patent (PCT/US12/55042) has been filed for the latter drug repurposing for SCD treatment. CONCLUSION: We developed the DESSCD resource dedicated to exploration of text-mined and data-mined information about SCD. No similar SCD-related resource exists. Thus, we anticipate that DESSCD will serve as a valuable tool for physicians and researchers interested in SCD.

Dragon exploration system on marine sponge compounds interactions.

BACKGROUND: Natural products are considered a rich source of new chemical structures that may lead to the therapeutic agents in all major disease areas. About 50% of the drugs introduced in the market in the last 20 years were natural products/derivatives or natural products mimics, which clearly shows the influence of natural products in drug discovery. RESULTS: In an effort to further support the research in this field, we have developed an integrative knowledge base on Marine Sponge Compounds Interactions (Dragon Exploration System on Marine Sponge Compounds Interactions - DESMSCI) as a web resource. This knowledge base provides information about the associations of the sponge compounds with different biological concepts such as human genes or proteins, diseases, as well as pathways, based on the literature information available in PubMed and information deposited in several other databases. As such, DESMSCI is aimed as a research support resource for problems on the utilization of marine sponge compounds. DESMSCI allows visualization of relationships between different chemical compounds and biological concepts through textual and tabular views, graphs and relational networks. In addition, DESMSCI has built in hypotheses discovery module that generates potentially new/interesting associations among different biomedical concepts. We also present a case study derived from the hypotheses generated by DESMSCI which provides a possible novel mode of action for variolins in Alzheimer's disease. CONCLUSION: DESMSCI is the first publicly available (http://www.cbrc.kaust.edu.sa/desmsci) comprehensive resource where users can explore information, compiled by text- and data-mining approaches, on biological and chemical data related to sponge compounds.

DESTAF: a database of text-mined associations for reproductive toxins potentially affecting human fertility.

The Dragon Exploration System for Toxicants and Fertility (DESTAF) is a publicly available resource which enables researchers to efficiently explore both known and potentially novel information and associations in the field of reproductive toxicology. To create DESTAF we used data from the literature (including over 10500 PubMed abstracts), several publicly available biomedical repositories, and specialized, curated dictionaries. DESTAF has an interface designed to facilitate rapid assessment of the key associations between relevant concepts, allowing for a more in-depth exploration of information based on different gene/protein-, enzyme/metabolite-, toxin/chemical-, disease- or anatomically centric perspectives. As a special feature, DESTAF allows for the creation and initial testing of potentially new association hypotheses that suggest links between biological entities identified through the database. DESTAF, along with a PDF manual, can be found at http://cbrc.kaust.edu.sa/destaf. It is free to academic and non-commercial users and will be updated quarterly.

Dragon exploratory system on hepatitis C virus (DESHCV).

Even though hepatitis C virus (HCV) cDNA was characterized about 20 years ago, there is insufficient understanding of the molecular etiology underlying HCV infections. Current global rates of infection and its increasingly chronic character are causes of concern for health policy experts. Vast amount of data accumulated from biochemical, genomic, proteomic, and other biological analyses allows for novel insights into the HCV viral structure, life cycle and functions of its proteins. Biomedical text-mining is a useful approach for analyzing the increasing corpus of published scientific literature on HCV. We report here the first comprehensive HCV customized biomedical text-mining based online web resource, dragon exploratory system on hepatitis C virus (DESHCV), a biomedical text-mining and relationship exploring knowledge base was developed by exploring literature on HCV. The pre-compiled dictionaries existing in the dragon exploratory system (DES) were enriched with biomedical concepts pertaining to HCV proteins, their name variants and symbols to make it suitable for targeted information exploration and knowledge extraction as focused on HCV. A list of 32,895 abstracts retrieved via PubMed database using specific keywords searches related to HCV were processed based on concept recognition of terms from several dictionaries. The web query interface enables retrieval of information using specified concepts, keywords and phrases, generating text-derived association networks and hypotheses, which could be tested to identify potentially novel relationship between different concepts. Such an approach could also augment efforts in the search for diagnostic or even therapeutic targets. DESHCV thus represents online literature-based discovery resource freely accessible for academic and non-profit users via http://apps.sanbi.ac.za/DESHCV/ and its mirror site http://cbrc.kaust.edu.sa/deshcv/.

DDPC: Dragon Database of Genes associated with Prostate Cancer.

Prostate cancer (PC) is one of the most commonly diagnosed cancers in men. PC is relatively difficult to diagnose due to a lack of clear early symptoms. Extensive research of PC has led to the availability of a large amount of data on PC. Several hundred genes are implicated in different stages of PC, which may help in developing diagnostic methods or even cures. In spite of this accumulated information, effective diagnostics and treatments remain evasive. We have developed Dragon Database of Genes associated with Prostate Cancer (DDPC) as an integrated knowledgebase of genes experimentally verified as implicated in PC. DDPC is distinctive from other databases in that (i) it provides pre-compiled biomedical text-mining information on PC, which otherwise require tedious computational analyses, (ii) it integrates data on molecular interactions, pathways, gene ontologies, gene regulation at molecular level, predicted transcription factor binding sites on promoters of PC implicated genes and transcription factors that correspond to these binding sites and (iii) it contains DrugBank data on drugs associated with PC. We believe this resource will serve as a source of useful information for research on PC. DDPC is freely accessible for academic and non-profit users via http://apps.sanbi.ac.za/ddpc/ and http://cbrc.kaust.edu.sa/ddpc/.

An atlas of combinatorial transcriptional regulation in mouse and man.

Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.

DDEC: Dragon database of genes implicated in esophageal cancer.

BACKGROUND: Esophageal cancer ranks eighth in order of cancer occurrence. Its lethality primarily stems from inability to detect the disease during the early organ-confined stage and the lack of effective therapies for advanced-stage disease. Moreover, the understanding of molecular processes involved in esophageal cancer is not complete, hampering the development of efficient diagnostics and therapy. Efforts made by the scientific community to improve the survival rate of esophageal cancer have resulted in a wealth of scattered information that is difficult to find and not easily amendable to data-mining. To reduce this gap and to complement available cancer related bioinformatic resources, we have developed a comprehensive database (Dragon Database of Genes Implicated in Esophageal Cancer) with esophageal cancer related information, as an integrated knowledge database aimed at representing a gateway to esophageal cancer related data. DESCRIPTION: Manually curated 529 genes differentially expressed in EC are contained in the database. We extracted and analyzed the promoter regions of these genes and complemented gene-related information with transcription factors that potentially control them. We further, precompiled text-mined and data-mined reports about each of these genes to allow for easy exploration of information about associations of EC-implicated genes with other human genes and proteins, metabolites and enzymes, toxins, chemicals with pharmacological effects, disease concepts and human anatomy. The resulting database, DDEC, has a useful feature to display potential associations that are rarely reported and thus difficult to identify. Moreover, DDEC enables inspection of potentially new 'association hypotheses' generated based on the precompiled reports. CONCLUSION: We hope that this resource will serve as a useful complement to the existing public resources and as a good starting point for researchers and physicians interested in EC genetics. DDEC is freely accessible to academic and non-profit users at http://apps.sanbi.ac.za/ddec/. DDEC will be updated twice a year.

Database for exploration of functional context of genes implicated in ovarian cancer.

Ovarian cancer (OC) is becoming the most common gynecological cancer in developed countries and the most lethal gynecological malignancy. It is also the fifth leading cause of all cancer-related deaths in women. The identification of diagnostic biomarkers and development of early detection techniques for OC largely depends on the understanding of the complex functionality and regulation of genes involved in this disease. Unfortunately, information about these OC genes is scattered throughout the literature and various databases making extraction of relevant functional information a complex task. To reduce this problem, we have developed a database dedicated to OC genes to support exploration of functional characterization and analysis of biological processes related to OC. The database contains general information about OC genes, enriched with the results of transcription regulation sequence analysis and with relevant text mining to provide insights into associations of the OC genes with other genes, metabolites, pathways and nuclear proteins. Overall, it enables exploration of relevant information for OC genes from multiple angles, making it a unique resource for OC and will serve as a useful complement to the existing public resources for those interested in OC genetics. Access is free for academic and non-profit users and database can be accessed at http://apps.sanbi.ac.za/ddoc/.