INDI-integrated nanobody database for immunoinformatics.
Ontology highlight
ABSTRACT:
SUBMITTER: Deszynski P
PROVIDER: S-EPMC8728276 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Polyglutamine (polyQ) diseases are neurodegenerative disorders caused by abnormally expanded Cytosine, Adenine, Guanine (CAG) triplet repeat sequences in the coding region of otherwise unrelated genes. Until now, nine different polyQ diseases have been described: Huntington's disease, dentatorubral-pallidoluysian atrophy, spinal and bulbar muscular atrophy and six types of spinocerebellar ataxias-1, 2, 3, 6, 7 and 17. The pathogenic expansion translates into an aberrant tract of glutamines in the encoded proteins, compromising several cellular functions and biological processes. There is currently no cure available for the progressive neurodegenerative disorders caused by the ensuing cytotoxic alterations. Although each disease is considered rare, polyQ diseases constitute the largest group of monogenic neurodegenerative disorders. Information about these disorders is scattered among several books, articles and general databases, hindering exploration by students and researchers, but also by patients and their families. Therefore, we aimed to develop a free online database to fill this gap, by centralizing relevant available information. The PolyQ Database is a platform that focuses on all nine polyQ diseases and offers information about topics that are pertinent for scientists, clinicians and the general public, including epidemiology, the characteristics of the causative genes and the codified proteins, the pathophysiology of the diseases and the main clinical manifestations. The database is available at https://polyq.pt/, and it is the first of its kind, focusing exclusively on this group of rare diseases. The database was conceived to be continuously updated and allow incorporation and dissemination of the latest information on polyQ diseases.
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Project description:Point-of-care testing (POCT) devices play a crucial role as tools for disease diagnostics, and the integration of biorecognition elements with electronic components into these devices widens their functionalities and facilitates the development of complex quantitative assays. Unfortunately, biosensors that exploit large conventional IgG antibodies to capture relevant biomarkers are often limited in terms of sensitivity, selectivity, and storage stability, considerably restricting the use of POCT in real-world applications. Therefore, we used nanobodies as they are more suitable for fabricating electrochemical biosensors with near-field communication (NFC) technology. Moreover, a flow-through microfluidic device was implemented in this system for the detection of C-reactive protein (CRP), an inflammation biomarker, and a model analyte. The resulting sensors not only have high sensitivity and portability but also retain automated sequential flow properties through capillary transport without the need for an external pump. We also compared the accuracy of CRP quantitative analyses between commercial PalmSens4 and NFC-based potentiostats. Furthermore, the sensor reliability was evaluated using three biological samples (artificial serum, plasma, and whole blood without any pretreatment). This platform will streamline the development of POCT devices by combining operational simplicity, low cost, fast analysis, and portability.
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Project description:Integrating cancer genes and markers with experimental evidence might provide valuable information for the further investigation of crosstalk between tumor genes and markers in cancer biology. To achieve this objective, we developed a database known as the Cancer Gene Marker Database (CGMD), which integrates data on tumor genes and markers based on experimental evidence. The major goal of CGMD is to provide the following: 1) current systematic treatment approaches and recent advances in different cancer treatments; 2) the aggregation of different genes and markers by their molecular characteristics and pathway associations; and 3) free access to the data compiled by CGMD at http://cgmd.in/. The database consists of 309 genes and 206 markers, as well as a list of 40 different human cancers, with detailed descriptions of all characterized markers. CGMD provides complete cancer annotations and molecular descriptions of cancer genes and markers such as CpG islands, promoters, exons, PDB structures, active sites and domains.
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Project description:BACKGROUND: Detoxification proteins are a class of proteins for degradation and/or elimination of endogenous and exogenous toxins or medicines, as well as reactive oxygen species (ROS) produced by these materials. Most of these proteins are generated as a response to the stimulation of toxins or medicines. They are essential for the clearance of harmful substances and for maintenance of physiological balance in organisms. Thus, it is important to collect and integrate information on detoxification proteins. RESULTS: To store, retrieve and analyze the information related to their features and functions, we developed the DetoxiProt, a comprehensive database for annotation of these proteins. This database provides detailed introductions about different classes of the detoxification proteins. Extensive annotations of these proteins, including sequences, structures, features, inducers, inhibitors, substrates, chromosomal location, functional domains as well as physiological-biochemical properties were generated. Furthermore, pre-computed BLAST results, multiple sequence alignments and evolutionary trees for detoxification proteins are also provided for evolutionary study of conserved function and pathways. The current version of DetoxiProt contains 5956 protein entries distributed in 628 organisms. An easy to use web interface was designed, so that annotations about each detoxification protein can be retrieved by browsing with a specific method or by searching with different criteria. CONCLUSIONS: DetoxiProt provides an effective and efficient way of accessing the detoxification protein sequences and other high-quality information. This database would be a valuable source for toxicologists, pharmacologists and medicinal chemists. DetoxiProt database is freely available at http://lifecenter.sgst.cn/detoxiprot/.
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Project description:A specialized orchid database, named Orchidstra (URL: http://orchidstra.abrc.sinica.edu.tw), has been constructed to collect, annotate and share genomic information for orchid functional genomics studies. The Orchidaceae is a large family of Angiosperms that exhibits extraordinary biodiversity in terms of both the number of species and their distribution worldwide. Orchids exhibit many unique biological features; however, investigation of these traits is currently constrained due to the limited availability of genomic information. Transcriptome information for five orchid species and one commercial hybrid has been included in the Orchidstra database. Altogether, these comprise >380,000 non-redundant orchid transcript sequences, of which >110,000 are protein-coding genes. Sequences from the transcriptome shotgun assembly (TSA) were obtained either from output reads from next-generation sequencing technologies assembled into contigs, or from conventional cDNA library approaches. An annotation pipeline using Gene Ontology, KEGG and Pfam was built to assign gene descriptions and functional annotation to protein-coding genes. Deep sequencing of small RNA was also performed for Phalaenopsis aphrodite to search for microRNAs (miRNAs), extending the information archived for this species to miRNA annotation, precursors and putative target genes. The P. aphrodite transcriptome information was further used to design probes for an oligonucleotide microarray, and expression profiling analysis was carried out. The intensities of hybridized probes derived from microarray assays of various tissues were incorporated into the database as part of the functional evidence. In the future, the content of the Orchidstra database will be expanded with transcriptome data and genomic information from more orchid species.
| S-EPMC3583029 | biostudies-literature
Project description:High-throughput screening based on CRISPR-Cas9 libraries has become an attractive and powerful technique to identify target genes for functional studies. However, accessibility of public data is limited due to the lack of user-friendly utilities and up-to-date resources covering experiments from third parties. Here, we describe iCSDB, an integrated database of CRISPR screening experiments using human cell lines. We compiled two major sources of CRISPR-Cas9 screening: the DepMap portal and BioGRID ORCS. DepMap portal itself is an integrated database that includes three large-scale projects of CRISPR screening. We additionally aggregated CRISPR screens from BioGRID ORCS that is a collection of screening results from PubMed articles. Currently, iCSDB contains 1375 genome-wide screens across 976 human cell lines, covering 28 tissues and 70 cancer types. Importantly, the batch effects from different CRISPR libraries were removed and the screening scores were converted into a single metric to estimate the knockout efficiency. Clinical and molecular information were also integrated to help users to select cell lines of interest readily. Furthermore, we have implemented various interactive tools and viewers to facilitate users to choose, examine and compare the screen results both at the gene and guide RNA levels. iCSDB is available at https://www.kobic.re.kr/icsdb/.
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Project description:BackgroundStomach cancer (SC) is a type of cancer, which is derived from the stomach mucous membrane. As there are non-specific symptoms or no noticeable symptoms observed at the early stage, newly diagnosed SC cases usually reach an advanced stage and are thus difficult to cure. Therefore, in this study, we aimed to develop an integrated database of SC.MethodsSC-related genes were identified through literature mining and by analyzing the publicly available microarray datasets. Using the RNA-seq, miRNA-seq and clinical data downloaded from The Cancer Genome Atlas (TCGA), the Kaplan-Meier (KM) survival curves for all the SC-related genes were generated and analyzed. The miRNAs (miRanda, miRTarget2, PicTar, PITA and TargetScan databases), SC-related miRNAs (HMDD and miR2Disease databases), single nucleotide polymorphisms (SNPs, dbSNP database), and SC-related SNPs (ClinVar database) were also retrieved from the indicated databases. Moreover, gene_disease (OMIM and GAD databases), copy number variation (CNV, DGV database), methylation (PubMeth database), drug (WebGestalt database), and transcription factor (TF, TRANSFAC database) analyses were performed for the differentially expressed genes (DEGs).ResultsIn total, 9990 SC-related genes (including 8347 up-regulated genes and 1643 down-regulated genes) were identified, among which, 65 genes were further confirmed as SC-related genes by performing enrichment analysis. Besides this, 457 miRNAs, 20 SC-related miRNAs, 1570 SNPs, 108 SC-related SNPs, 419 TFs, 44,605 CNVs, 3404 drug-associated genes, 63 genes with methylation, and KM survival curves of 20,264 genes were obtained. By integrating these datasets, an integrated database of stomach cancer, designated as SCDb, (available at http://www.stomachcancerdb.org/) was established.ConclusionsAs a comprehensive resource for human SC, SCDb database will be very useful for performing SC-related research in future, and will thus promote the understanding of the pathogenesis of SC.
| S-EPMC7265634 | biostudies-literature