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At least 595 records · Page 33Linked to original sources
PubMed2026

Furmonertinib inhibits non-small cell lung cancer progression through ANGPT1-mediated regulation of cell migration and apoptosis.

BACKGROUND: Lung cancer remains one of the leading causes of cancer-related mortality worldwide, highlighting the urgent need for effective therapeutic agents. This study investigates the antitumor effects and underlying mechanisms of furmonertinib (FUR) in lung cancer cells. METHODS: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to identify FUR target genes, followed by functional enrichment, survival, and protein-protein interaction (PPI) network analyses. Human lung cancer cell line A549 was treated with FUR and/or ANGPT1-specific siRNA. Cell migration, apoptosis, and protein expression were assessed by wound healing, flow cytometry, and Western blotting. Cellular thermal shift assay (CETSA) and drug affinity response target stability (DARTS) assays were used to assess FUR-induced stabilization of angiopoietin-1 (ANGPT1) protein. RESULTS: FUR treatment significantly inhibited cell migration and increased apoptosis in NSCLC cells. Bioinformatics analysis revealed 12 overlapping target genes of FUR from the PharmMapper and SwissTargetPrediction databases, with ANGPT1 emerging as a key candidate. ANGPT1 expression was downregulated in tumor tissues and positively correlated with patient survival. Western blotting confirmed that FUR upregulated ANGPT1 protein levels in a dose-dependent manner. Knockdown of ANGPT1 enhanced migration and suppressed apoptosis, while FUR reversed these effects. FUR treatment enhanced the stability of ANGPT1 under high-temperature conditions while reducing its sensitivity to protease. ANGPT1 may have affected tumor cell migration through cell adhesion and extracellular matrix (ECM) pathways. CONCLUSIONS: FUR suppresses lung cancer progression by upregulating ANGPT1, thereby inhibiting cell migration and promoting apoptosis. ANGPT1 is a potential therapeutic target and provides new insights into the anti-tumor mechanism of FUR in lung cancer.

Lung cancer↗
PubMed2003

Signal transduction-related bioinformatics services.

Signal transduction pathways are crucial for the regulation of a very wide variety of cellular functions ranging, for example, from translation to intercellular communication, and from metabolism to apoptosis. Protein kinases and phosphatases, together with their binding partners, are key players in these cascades. They also form a substantial part of the genes in genomes and proteins in proteomes in all animals. Signalling can be studied in many different levels and ways. This has resulted in large body of publications and Internet services. This paper describes open-access databases and software aiming at presenting the kind of data available and how to perform bioinformatics analyses.

Computational Biology↗
PubMed2003

iMap: a database-driven utility to integrate and access the genetic and physical maps of maize.

MOTIVATION: Because of the unique biological features, a bioinformatic platform for the integrated genetic and physical map of maize is required for storing, integrating, accessing and visualizing the underlying data. RESULTS: The goal of the Maize Mapping Project is to develop a fully integrated genetic and physical map for maize. To display this integrated map, we have developed iMap. iMap has three main components: a relational database (iMapDB), a map graphic browser (iMap Viewer) and a search utility (iMap Search). iMapDB is populated with current genetic and physical map data, describing relationships among genetic loci, molecular markers and bacterial artificial chromosome (BAC) contigs. The database also contains integrated information produced by applying a set of anchoring rules to assign BAC contigs to specific locations on the genetic map. The iMap Viewer and iMap Search functions are combined in the user interface to allow viewing and retrieving many types of genetic and physical map data. The iMap Viewer features side-by-side chromosome-based displays of the genetic map and associated BAC contigs. For each genetic locus, information about marker type or contig can be viewed via pop-up windows that feature links to external data resources. Searches can be conducted for genetic locus, probe or sequence accession number; search results include relevant map positions, anchored BAC contigs and links to the graphical display of relevant chromosomes. iMap can be accessed at http://www.maizemap.org AVAILABILITY: The iMap utility package is available for non-commercial use upon request from the authors.

Chromosome Mapping↗
PubMed2001

HUNT: launch of a full-length cDNA database from the Helix Research Institute.

The Helix Research Institute (HRI) in Japan is releasing 4356 HUman Novel Transcripts and related information in the newly established HUNT database. The institute is a joint research project principally funded by the Japanese Ministry of International Trade and Industry, and the clones were sequenced in the governmental New Energy and Industrial Technology Development Organization (NEDO) Human cDNA Sequencing Project. The HUNT database contains an extensive amount of annotation from advanced analysis and represents an essential bioinformatics contribution towards understanding of the gene function. The HRI human cDNA clones were obtained from full-length enriched cDNA libraries constructed with the oligo-capping method and have resulted in novel full-length cDNA sequences. A large fraction has little similarity to any proteins of known function and to obtain clues about possible function we have developed original analysis procedures. Any putative function deduced here can be validated or refuted by complementary analysis results. The user can also extract information from specific categories like PROSITE patterns, PFAM domains, PSORT localization, transmembrane helices and clones with GENIUS structure assignments. The HUNT database can be accessed at http://www.hri.co.jp/HUNT.

Computational Biology↗
PubMed1999

Genomes OnLine Database (GOLD 1.0): a monitor of complete and ongoing genome projects world-wide.

UNLABELLED: GOLD (Genomes On Line Database) is a World Wide Web resource for comprehensive access to information regarding complete and ongoing genome projects around the world. AVAILABILITY: GOLD is based at the University of Illinois at Urbana-Champaign and is available at http://geta.life.uiuc.edu/ approximately nikos/genomes. html. It is also mirrored at the European Bioinformatics Institute at http://www.ebi.ac.uk/research/cgg/genomes.html. CONTACT: genomes@ebi.ac.uk

Databases, Factual↗
PubMed2006

A high level interface to SCOP and ASTRAL implemented in python.

BACKGROUND: Benchmarking algorithms in structural bioinformatics often involves the construction of datasets of proteins with given sequence and structural properties. The SCOP database is a manually curated structural classification which groups together proteins on the basis of structural similarity. The ASTRAL compendium provides non redundant subsets of SCOP domains on the basis of sequence similarity such that no two domains in a given subset share more than a defined degree of sequence similarity. Taken together these two resources provide a 'ground truth' for assessing structural bioinformatics algorithms. We present a small and easy to use API written in python to enable construction of datasets from these resources. RESULTS: We have designed a set of python modules to provide an abstraction of the SCOP and ASTRAL databases. The modules are designed to work as part of the Biopython distribution. Python users can now manipulate and use the SCOP hierarchy from within python programs, and use ASTRAL to return sequences of domains in SCOP, as well as clustered representations of SCOP from ASTRAL. CONCLUSION: The modules make the analysis and generation of datasets for use in structural genomics easier and more principled.

Database Management Systems↗
PubMed2000

The role of pattern databases in sequence analysis.

In the wake of the numerous now-fruitful genome projects, we are entering an era rich in biological data. The field of bioinformatics is poised to exploit this information in increasingly powerful ways, but the abundance and growing complexity both of the data and of the tools and resources required to analyse them are threatening to overwhelm us. Databases and their search tools are now an essential part of the research environment. However, the rate of sequence generation and the haphazard proliferation of databases have made it difficult to keep pace with developments. In an age of information overload, researchers want rapid, easy-to-use, reliable tools for functional characterisation of newly determined sequences. But what are those tools? How do we access them? Which should we use? This review focuses on a particular type of database that is increasingly used in the task of routine sequence analysis--the so-called pattern database. The paper aims to provide an overview of the current status of pattern databases in common use, outlining the methods behind them and giving pointers on their diagnostic strengths and weaknesses.

Amino Acid Motifs↗
PubMed2026

CD44 gene rs9666607 polymorphism is associated with papillary thyroid carcinoma and interacts with CREB3L1.

BACKGROUND: The incidence of papillary thyroid carcinoma (PTC) has been rising. CD44 is involved in cell adhesion and migration, but the role of its genetic variation in PTC remains unclear. METHODS: This study aimed to investigate the association of CD44 gene polymorphisms with PTC and to examine the interaction between CD44 and CREB3L1. This study enrolled 354 patients with PTC, and the genotype distribution of the CD44 polymorphism (rs9666607) was analyzed. Key PTC genes were screened using the Gene Expression Omnibus (GEO) database (GSE33630). Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed on these key genes. CD44 expression was validated using TCGA database, ELISA, qRTPCR, Western blot, and IHC in patient tissues, PTC mouse model, and human cell lines. The direct interactive molecules were screened through a bioinformatics method. RESULTS: The GSE33630 dataset identified a total of 124 upregulated and 85 downregulated differentially expressed genes. Enrichment analysis revealed 12 key PTC genes, including CD44. TCGA database validation revealed that CD44 was significantly overexpressed in PTC patients. The rs9666607‑A allele was associated with an increased risk of PTC and lymph node metastasis under a dominant model. CD44 mRNA and protein levels were significantly higher in PTC tissues versus adjacent tissue and further elevated in metastatic cases. Bioinformatic analysis predicted CD44 interaction with the transcription factor CREB3L1, and this was confirmed by molecular docking. CREB3L1 expression was synchronously upregulated with CD44 in PTC. CONCLUSION: CD44 polymorphisms, particularly the rs9666607-A allele, are significantly associated with PTC risk and metastasis in the studied population. CD44 is overexpressed in PTC, and its interaction with CREB3L1 suggests a potential novel interaction in PTC pathogenesis.

Hyaluronan Receptors↗
PubMed2002

Tolerating some redundancy significantly speeds up clustering of large protein databases.

MOTIVATION: Sequence clustering replaces groups of similar sequences in a database with single representatives. Clustering large protein databases like the NCBI Non-Redundant database (NR) using even the best currently available clustering algorithms is very time-consuming and only practical at relatively high sequence identity thresholds. Our previous program, CD-HI, clustered NR at 90% identity in approximately 1 h and at 75% identity in approximately 1 day on a 1 GHz Linux PC (Li et al., Bioinformatics, 17, 282, 2001); however even faster clustering speed is needed because the size of protein databases are rapidly growing and many applications desire a lower attainable thresholds. RESULTS: For our previous algorithm (CD-HI), we have employed short-word filters to speed up the clustering. In this paper, we show that tolerating some redundancy makes for more efficient use of these short-word filters and increases the program's speed 100 times. Our new program implements this technique and clusters NR at 70% identity within 2 h, and at 50% identity in approximately 5 days. Although some redundancy is present after clustering, our new program's results only differ from our previous program's by less than 0.4%.

Algorithms↗
PubMed2001

Recent advances in computational genomics.

In the post-genomic era, the new discipline of functional genomics is now facing the challenge of associating a function (as well as estimating its relevance to industrial applications) to about 100,000 microbial, plant or animal genes of known sequence but unknown function. Besides the design of databases, computational methods are increasingly becoming intimately linked with the various experimental approaches. Consequently, bioinformatics is rapidly evolving into independent fields addressing the specific problems of interpreting i) genomic sequences, ii) protein sequences and 3D-structures, as well as iii) transcriptome and macromolecular interaction data. It is thus increasingly difficult for the biologist to choose the computational approaches that perform best in these various areas. This paper attempts to review the most useful developments of the last 2 years.

Computational Biology↗
PubMed2002

The EMBL Nucleotide Sequence Database.

The EMBL Nucleotide Sequence Database (aka EMBL-Bank; http://www.ebi.ac.uk/embl/) incorporates, organises and distributes nucleotide sequences from all available public sources. EMBL-Bank is located and maintained at the European Bioinformatics Institute (EBI) near Cambridge, UK. In an international collaboration with DDBJ (Japan) and GenBank (USA), data are exchanged amongst the collaborating databases on a daily basis. Major contributors to the EMBL database are individual scientists and genome project groups. Webin is the preferred web-based submission system for individual submitters, whilst automatic procedures allow incorporation of sequence data from large-scale genome sequencing centres and from the European Patent Office (EPO). Database releases are produced quarterly. Network services allow free access to the most up-to-date data collection via FTP, email and World Wide Web interfaces. EBI's Sequence Retrieval System (SRS), a network browser for databanks in molecular biology, integrates and links the main nucleotide and protein databases plus many other specialized databases. For sequence similarity searching, a variety of tools (e.g. Blitz, Fasta, BLAST) are available which allow external users to compare their own sequences against the latest data in the EMBL Nucleotide Sequence Database and SWISS-PROT. All resources can be accessed via the EBI home page at http://www.ebi.ac.uk.

Animals↗
PubMed2006

The LIFEdb database in 2006.

LIFEdb (http://www.LIFEdb.de) integrates data from large-scale functional genomics assays and manual cDNA annotation with bioinformatics gene expression and protein analysis. New features of LIFEdb include (i) an updated user interface with enhanced query capabilities, (ii) a configurable output table and the option to download search results in XML, (iii) the integration of data from cell-based screening assays addressing the influence of protein-overexpression on cell proliferation and (iv) the display of the relative expression ('Electronic Northern') of the genes under investigation using curated gene expression ontology information. LIFEdb enables researchers to systematically select and characterize genes and proteins of interest, and presents data and information via its user-friendly web-based interface.

Cell Proliferation↗
PubMed2005

Plant membrane proteome databases.

In all living organisms transmembrane (TM) proteins are crucially involved in many physiological processes and constitute 20-30% of the proteome. An important class of TM proteins are transporters that interconnect biochemical pathways across the plasma membrane and intracellular membranes, e.g. the mitochondrial membranes and chloroplast envelope membranes. In recent years, bioinformatical tools to predict TM domains and subcellular localization were developed and used to analyze the first complete plant genomes of Arabidopsis and rice. This review focuses on plant TM proteome databases that compile topology and intracellular targeting predictions and different kinds of experimental data. In addition, other web sites are discussed that contribute useful experimental and/or bioinformatical data.

Arabidopsis↗
PubMed2025

Identification and validation of the important role of KIF11 in the development and progression of endometrial cancer.

BACKGROUND: Human kinesin family member 11 (KIF11) plays a vital role in regulating the cell cycle and is implicated in the tumorigenesis and progression of various cancers, but its role in endometrial cancer (EC) is still unclear. Our current research explored the prognostic value, biological function and targeting strategy of KIF11 in EC through approaches including bioinformatics, machine learning and experimental studies. METHODS: The GSE17025 dataset from the GEO database was analyzed via the limma package to identify differentially expressed genes (DEGs) in EC. Functional enrichment analysis of the DEGs was conducted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. DEGs were further screened for hub genes through protein-protein interaction (PPI) network analysis and machine learning. The role of the hub gene KIF11 in EC was analyzed using clinical data from the TCGA database. The expression of KIF11 in EC was subsequently validated in clinical samples. In vitro experiments were utilized to evaluate the effects of KIF11 on biological functions such as proliferation, migration, apoptosis, and the cell cycle in endometrial cancer cells. RESULTS: A total of 877 DEGs, which are widely involved in important biological processes such as cell division, tubulin binding, and the cell cycle, were identified. Through PPI network analysis and machine learning, KIF11 was selected as the hub gene for subsequent analysis and experimental validation. An analysis of TCGA data revealed that KIF11 is highly expressed in EC and is associated with tumor grade, stage, and a low survival rate. The overexpression of KIF11 in tumor tissues was further confirmed in EC patient samples. KIF11 knockdown had inhibitory effects on cell proliferation, migration and invasion. Flow cytometry analysis revealed that KIF11 knockdown induced G2/M phase arrest and promoted apoptosis in EC cells. CONCLUSION: Our study demonstrated that KIF11 was upregulated in EC and was strongly associated with a poor prognosis. Notably, we found that reduced KIF11 expression inhibited EC cell proliferation, migration and invasion. KIF11 knockdown caused more EC cells to arrest in the G2/M phase and undergo apoptosis. The findings of our study emphasized that KIF11 may be a promising prognostic biomarker and therapeutic target for EC patients.

Humans↗
PubMed2003

The UCSC Genome Browser Database.

The University of California Santa Cruz (UCSC) Genome Browser Database is an up to date source for genome sequence data integrated with a large collection of related annotations. The database is optimized to support fast interactive performance with the web-based UCSC Genome Browser, a tool built on top of the database for rapid visualization and querying of the data at many levels. The annotations for a given genome are displayed in the browser as a series of tracks aligned with the genomic sequence. Sequence data and annotations may also be viewed in a text-based tabular format or downloaded as tab-delimited flat files. The Genome Browser Database, browsing tools and downloadable data files can all be found on the UCSC Genome Bioinformatics website (http://genome.ucsc.edu), which also contains links to documentation and related technical information.

Animals↗
PubMed2006

snoRNA-LBME-db, a comprehensive database of human H/ACA and C/D box snoRNAs.

The snoRNA-LBME-db is a dedicated database containing human C/D box and H/ACA box small nucleolar RNAs (snoRNAs), and small Cajal body-specific RNAs (scaRNAs). C/D box and H/ACA box snoRNAs are part of ribonucleoparticles that guide 2'-O-ribose methylation and pseudouridilation, respectively, of selected residues of 28S, 18S or 5.8S rRNAs or of the spliceosomal U6 RNA. Similarly, scaRNAs guide modifications of the spliceosomal RNAs transcribed by RNA polymerase II (U1, U2, U4, U5 and U12) and are often composed of both C/D box and H/ACA box domains. However, some snoRNAs do not function as modification guide RNAs, but rather as RNA chaperones during the maturation of pre-rRNA. The database was built by a compilation of the literature, and comprises human sno/scaRNAs that were experimentally verified, as well as the human orthologs of snoRNAs that were cloned in other vertebrate species, and some snoRNAs that are predicted by bioinformatics search in loci submitted to genomic imprinting, but have not all been experimentally verified. For each entry, the database identifies the modified nucleotide(s) in the target RNA(s), indicates the corresponding predicted base pairing, gives a few pertinent references and provides a link to the position of the sno/scaRNA on the UCSC Genome Browser. The 'Find guide RNA' function allows one to find the sno/scaRNAs predicted to guide the modification of a particular nucleotide in the rRNA and spliceosomal RNA sequences. The 'Browse' function allows one to download the sequences of selected sno/scaRNAs in the FASTA format. The database is available online at http://www-snorna.biotoul.fr/. It can also be accessed from the human UCSC Genome Browser via the sno/miRNA track.

Animals↗
PubMed2004

Telemedical database of Hodgkin's disease.

The creation of a complex telemedical system oriented towards childhood Hodgkin's disease has been undertaken at the Department of Bioinformatics and Telemedicine of the Jagiellonian University Medical College in cooperation with the Department of Oncology and Pediatric Hematology of the Polish-American Institute of Pediatrics, JU MC. Data collecting, data processing and data transmission is aimed to aid and/or supervise surgical and drug treatment. The Tele-Database of Childhood Hodgkin's Disease (TDCHD) is not a simple Internet database project. A few hundred data items are presented in each patient's record, covering the complete medical treatment period. Efficient management and proper data protection are necessary for a medical database. Therefore, the interface for entering data has been divided into several parts. Each part is subjected to separate editing and transfer. A double-layer debugging system has been applied in the program: the first pass occurs on the client side (programmed in JavaScript and XML), the second - on the server side (programmed in PHP). Strict authorization is requested for all participants. Clinical data collected according to management standards and information governance (data quality, security and confidentiality) is organized in a way that facilitates practical and scientific use.

Child↗
PubMed2006

Integrating protein structures and precomputed genealogies in the Magnum database: examples with cellular retinoid binding proteins.

BACKGROUND: When accurate models for the divergent evolution of protein sequences are integrated with complementary biological information, such as folded protein structures, analyses of the combined data often lead to new hypotheses about molecular physiology. This represents an excellent example of how bioinformatics can be used to guide experimental research. However, progress in this direction has been slowed by the lack of a publicly available resource suitable for general use. RESULTS: The precomputed Magnum database offers a solution to this problem for ca. 1,800 full-length protein families with at least one crystal structure. The Magnum deliverables include 1) multiple sequence alignments, 2) mapping of alignment sites to crystal structure sites, 3) phylogenetic trees, 4) inferred ancestral sequences at internal tree nodes, and 5) amino acid replacements along tree branches. Comprehensive evaluations revealed that the automated procedures used to construct Magnum produced accurate models of how proteins divergently evolve, or genealogies, and correctly integrated these with the structural data. To demonstrate Magnum's capabilities, we asked for amino acid replacements requiring three nucleotide substitutions, located at internal protein structure sites, and occurring on short phylogenetic tree branches. In the cellular retinoid binding protein family a site that potentially modulates ligand binding affinity was discovered. Recruitment of cellular retinol binding protein to function as a lens crystallin in the diurnal gecko afforded another opportunity to showcase the predictive value of a browsable database containing branch replacement patterns integrated with protein structures. CONCLUSION: We integrated two areas of protein science, evolution and structure, on a large scale and created a precomputed database, known as Magnum, which is the first freely available resource of its kind. Magnum provides evolutionary and structural bioinformatics resources that are useful for identifying experimentally testable hypotheses about the molecular basis of protein behaviors and functions, as illustrated with the examples from the cellular retinoid binding proteins.

Amino Acid Sequence↗