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At least 1,099 records · Page 61Linked to original sources
PubMed2006

An object-oriented programming system for the integration of internet-based bioinformatics resources.

The Internet consists of a vast inhomogeneous reservoir of data. Developing software that can integrate a wide variety of different data sources is a major challenge that must be addressed for the realisation of the full potential of the Internet as a scientific research tool. This article presents a semi-automated object-oriented programming system for integrating web-based resources. We demonstrate that the current Internet standards (HTML, CGI [common gateway interface], Java, etc.) can be exploited to develop a data retrieval system that scans existing web interfaces and then uses a set of rules to generate new Java code that can automatically retrieve data from the Web. The validity of the software has been demonstrated by testing it on several biological databases. We also examine the current limitations of the Internet and discuss the need for the development of universal standards for web-based data.

Computational Biology↗
PubMed2026

Identification of Critical Genes Related to Breast Cancer with Brain Metastasis Through Bioinformatics Analysis.

INTRODUCTION: Distant metastasis accounts for the majority of Breast Cancer (BC)-related mortality. The brain is one of the most common regions of metastasis. However, the underlying molecular mechanisms remain uncertain. METHODS: In this study, gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. Datasets GSE100534 and GSE52604, containing 16 primary brain tumor samples and 38 breast cancer brain metastasis samples, were used to identify the Differentially Expressed Genes (DEGs). The Metascape database was used to analyze enriched Gene Ontology (GO) entries and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway entries in DEGs. The STRING database was then used to construct a Protein-Protein Interaction (PPI) network, and the Cytoscape platform was employed to visualize the network. Furthermore, the Kaplan-Meier curve was used to analyze the Relapse-Free Survival (RFS) among the hub genes. Finally, the iRegulon plugin was used to construct a regulatory network to find the transcription factors (TFs) that regulate the expression of the hub genes. RESULTS: A total of 344 DEGs, including 182 up-regulated and 162 down-regulated genes, were identified by using the limma package in R. A module with 18 nodes and 9 hub genes was selected from the PPI network by using the plugins MCODE and Cyto- Hubba, respectively. KEGG pathway analysis demonstrated that brain metastasis in BC was closely related to the oocyte cell cycle. The Kaplan-Meier curve showed that high expression of these 9 hub genes was associated with poor RFS in BC patients. TFs' analysis showed that E2F4, SIN3A, FOXM1, and TFDP1 interacted with these hub genes. DISCUSSION: This study revealed that Breast Cancer Brain Metastasis (BCBM) may have a promoting effect on the cell cycle of oocytes and affect the maturation and division of oocytes through the KEGG and GO analyses of 344 DEGs. The selected 9 hub genes (ASPM, BUB1, BUB1B, CCNA2, CCNB1, CDK1, NDC80, NCAPG, and TOP2A) and 4 transcription factors (E2F4, SIN3A, FOXM1, TFDP1) may play a critical role in brain metastasis of BC. CONCLUSION: The results of this study may aid in the early diagnosis and suggest potential targets for the treatment of BCBM.

Brain Neoplasms↗
PubMed2006

Web-ware bioinformatical analysis and structure modelling of N-terminus of human multisynthetase complex auxiliary component protein p43.

Human multisynthetase complex auxiliary component, protein p43 is an endothelial monocyte-activating polypeptide II precursor. In this study, comprehensive sequence analysis of N-terminus has been performed to identify structural domains, motifs, sites of post-translation modification and other functionally important parameters. The spatial structure model of full-chain protein p43 is obtained.

Amino Acid Motifs↗
PubMed2006

Recent developments of the chemistry development kit (CDK) - an open-source java library for chemo- and bioinformatics.

The Chemistry Development Kit (CDK) provides methods for common tasks in molecular informatics, including 2D and 3D rendering of chemical structures, I/O routines, SMILES parsing and generation, ring searches, isomorphism checking, structure diagram generation, etc. Implemented in Java, it is used both for server-side computational services, possibly equipped with a web interface, as well as for applications and client-side applets. This article introduces the CDK's new QSAR capabilities and the recently introduced interface to statistical software.

Computational Biology↗
PubMed2005

Progress in protein structural class prediction and its impact to bioinformatics and proteomics.

The structural class is an important attribute used to characterize the overall folding type of a protein or its domain. Since the concept of protein structural class was developed about 3 decades ago based on a visual inspection of polypeptide chain topologies in a dataset of only 31 gloular proteins, the number of structure-known proteins has been increased rapidly. For example, as of 12-July-2005, the entries deposited into RCSB PDB Protein Data Bank for proteins, peptides, and viruses whose 3-dimensional structures were determined by X-ray and NMR techniques have been increased to 28,920. To properly cover more and more structure-known proteins, some modification and expansion from the original structural classification scheme have been developed. Meanwhile, many different approaches have been proposed for predicting the structural class of proteins. In this review, the new classification schemes are briefly introduced. The attention is focused on the progress in structural class prediction and its impact in stimulating the development of identifying the other attributes of proteins. It is interesting to point out that the development of the latter has actually in turn greatly enriched the power of the former. Also, some promising approaches for the further development of protein structural class prediction are also addressed.

Computational Biology↗
PubMed2002

Hepatitis C virus proteins as targets for drug development: the role of bioinformatics and modelling.

Hepatitis C virus (HCV), a member of the Flaviviridae family, has been recognised to be responsible for both parenterally transmitted and sporadic non-A and non-B hepatitis affecting 1-3% of the world population. HCV is a positive stranded RNA virus encoding a single polyprotein which contains at least ten unique structural and non-structural proteins. Amongst these the structural protein E2 has been of special interest for vaccine development and the serine protease NS3, which is responsible for cleavage of the polyprotein, for the development of small molecule inhibitors. We will focus on the contribution of computational techniques and the use of structural information for the design and discovery of novel therapeutic agents for these targets. Both drug discovery and vaccine design efforts will be discussed taking into account also the problem of emerging resistance.

Computational Biology↗
PubMed2002

Bioinformatics and the discovery of novel anti-microbial targets.

Genomic research is playing a critical role in the discovery of new anti-microbial drugs. The rapid increase in bacterial and eukaryotic genome sequences allows for new and innovative ways for obtaining antimicrobial protein targets. Here, we describe a two level strategy for target identification and validation using computers (in silico). First, large scale comparative analyses of genome sequences were used to identify highly conserved genes which might be essential for in vitro and/or in vivo survival of bacterial pathogens. Lab-based experiments provided confirmation or validation of the hypothesis of in silico essentiality for over 350 individual genes. Over 200 validated, broad spectrum; yet highly specific gene targets, were identified in community infection pathogens. The second part of the target discovery strategy is an in-depth evolutionary, structural and cellular analysis of key drug targets. As an example, phylogenetic and structural analyses suggest that sequence and binding-pocket conservation in FabH (beta-ketoacyl-ACP synthase III) would allow for the development of small molecule inhibitors not only effective against a broad species spectrum of community bacterial pathogens but also as potential new therapies for tuberculosis and malaria.

Animals↗
PubMed2005

Application of bioinformatics in search for cleavable peptides of SARS-CoV M(pro) and chemical modification of octapeptides.

According to the "distorted key" theory as elaborated in a review article years ago (Chou, K.C.: Analytical Biochemistry, 1996, 233, 1-14), the knowledge of the cleavable peptides by SARS-CoV M(pro) (severe acute respiratory syndrome coronavirus main proteinase) can provide very useful insights on developing drugs against SARS. In view of this, the softwares, ZCURVE_CoV 1.0 and ZCURVE_CoV 2.0 (http://tubic.tju.edu.cn/sars/), developed recently for SARS-Coronavirus are used to analyze the 36 complete SARS-Coronavirus RNA sequences in the gene bank NCBI (http://www.ncbi.nlm.nih.gov/) from different sources for protein coding genes, and to search for the cleavage sites of SARS-CoV M(pro) in polyproteins pp1a and pp1ab. A total of 396 cleavage points are found in the 36 SARS-Coronavirus and 11 cleavable octapeptides abstracted from the 396 cleavage sites. The statistical distributions of amino acids for the cleavable octapeptides at the subsites R4, R3, R2, R1, R1', R2', R3' and R4' are calculated. The cleavage-specific positions are on R2, R1 and R1', and the positions R3 and R4 are featured by some certain specificity for SARS-CoV M(pro). The structural characters of amino acid residues around the cleavage-specific positions are discussed. Two most promising octapeptides, i.e., NH(2)-ATLQ downward arrowAIAS-COOH and NH(2)-ATLQ downward arrowAENV-COOH, are selected to be the candidates for chemical modification, converting into the inhibitors of SARS-CoV M(pro). A possible strategy to convert a cleavable octapeptide by SARS enzyme into a drug candidate against SARS is elucidated.

Amino Acid Sequence↗
PubMed2004

[Sequence variation of HIV and bioinformatics].

The envelope glycoprotein of human immunodeficiency virus type 1 (HIV-1) interacts with receptors on the target cell and mediates virus entry by fusing the viral and cell membranes. To maintain the viral infectivity, amino acids that interact with receptors are expected to be more conserved than the other sites on the protein surface. In contrast to the functional constraint of amino acids for the receptor binding, some amino acid changes in this protein may produce antigenic variations that enable the virus to escape from recognition of the host immune system. Therefore, both positive selection (higher fitness) and negative selection (lower fitness) against amino acid changes are taking place during evolution of surface proteins of parasites To elucidate the evolutionary mechanisms of the whole HIV-1 gp120 envelope glycoprotein at the single site level, we collected and analyzed all available sequence data for the protein. By analyzing 186 sequences of the HIV-1 gp120 (subtype B), we reevaluated amino acid variability at the single site level, and estimated the numbers of synonymous and nonsynonymous substitutions at each codon position to detect positive and negative selection. We identified 33 amino acid positions which may be under positive selection. Some of these positions may form discontinuous epitopes. We also analyzed amino acid sequences to find amino acid positions responsible for usage of the second receptor. We found that, in addition to the V3 loop, amino acid variation at residue 440 in C4 region is clearly linked with the usage of CXCR 4.

Amino Acid Sequence↗
PubMed2003

The urea transporter (UT) family: bioinformatic analyses leading to structural, functional, and evolutionary predictions.

We have identified all currently sequenced members of the urea transporter (UT) family (TC #1.A.28). Homologues occur exclusively in vertebrate animals and bacteria but not in other eukaryotic kingdoms or archaea. Sequence, structural, and phylogenetic analyses reveal conserved regions and residues and suggest that a primordial 5 transmembrane helical segment (TMS)-encoding genetic element duplicated to give a 10 TMS-encoding element early during evolutionary history, at about the time when eukaryotes diverged from prokaryotes. Two well-conserved, strongly amphipathic, putative alpha-helices that precede both 5 TMS repeat elements are predicted to be of structural, functional, or biogenic significance. A second duplication event (or a gene fusion event) occurred during development of the vertebrate lineage, giving rise to 20 TMS mammalian homologues. The results suggest that vertebrates acquired UT genetic information from bacteria only once and that all current orthologues and paralogues in the animal kingdom arose from this one primordial system.

Amino Acid Sequence↗
PubMed2004

Genetic, genomic, and bioinformatic tools for studying breast cancer progression.

Cancer susceptibility is a complex interaction of an individual's genetic composition and environmental exposures. Huge strides have been made in understanding cancer over the past 100 years, from the recognition of cancer as a genetic disease, to the identification of specific carcinogens, isolation of oncogenes and the recognition of tumor suppressors. Analysis of high-risk familial cancers has led to the discovery of new tumor suppressor genes and important cancer pathways. These families however represent only a small fraction of cancer in the general population. Most cancer instead probably results of an intricate interaction of polymorphic susceptibility genes with the sea of environmental exposures that humans experience. Although the central cadre of cancer genes is known, little is understood about the peripheral genes that likely comprise the polymorphic susceptibility loci. The challenge for cancer genetics is therefore to move forward from the Mendelian genetics of the rare familial cancer syndromes into the field of quantitative trait loci, susceptibility factors, and modifier genes. By identifying the genes that modulate an individual's susceptibility to cancer after an environmental exposure, researchers will be able to gain important insights into human biology, cancer prevention and treatment. The most efficient strategies to identify and characterize modifier loci will likely be those that are transdisciplinary, encompassing a variety of different "-omic" technologies. The application of a "trans-omic" techniques in our laboratory to the study of breast cancer dissemination is presented here as an illustration of the strategy.

Journal Article↗
PubMed2026

Expanding the Genomic Spectrum of NHLRC2-Associated FINCA Disease: Integrated Bioinformatic Characterization of a Novel Deep Intronic Variant Predicted to Activate a Pseudoexon.

NHLRC2-associated FINCA disease is an ultra-rare autosomal recessive multisystem disorder caused by biallelic pathogenic variants in NHLRC2. Its mutational spectrum and genotype-phenotype correlations remain incompletely defined, and the contribution of non-coding variants is poorly understood. Here, we report a male infant with a severe FINCA-like phenotype, including early-onset hemolytic anemia, pulmonary involvement, neurodevelopmental impairment, growth failure, recurrent infections, and fatal progression at 8.5 months. Whole-genome sequencing identified a compound heterozygous NHLRC2 genotype comprising the previously reported pathogenic missense variant c.442G>T (p.Asp148Tyr) and a novel deep intronic variant, c.331+6863A>G. Segregation analysis confirmed inheritance from different parents. Integrated genomic and splicing analysis predicted that c.331+6863A>G creates a strong cryptic donor splice site and supports pseudoexon inclusion. Reconstruction of the predicted aberrant transcript indicated premature termination and potential susceptibility to nonsense-mediated mRNA decay. To our knowledge, this is the first reported deep intronic NHLRC2 variant predicted to activate pseudoexon inclusion. Although experimental validation was unavailable, convergent clinical, segregation, population, and computational evidence supports c.331+6863A>G as the most plausible second disease-associated allele. This case expands the genomic spectrum of NHLRC2-associated FINCA disease and highlights the diagnostic value of phenotype-driven whole-genome sequencing.

Humans↗
PubMed2006

Bioinformatic approach for understanding the heterogeneity of cholangiocytes.

It is remarkable that microarray technologies have nearly reached a pinnacle. Establishment of further analysis and management of enormous data derived from microarray technology is currently the highest priority. The heterogeneous functions of cholangiocytes regulate the pathophysiology of the biliary epithelium in relation to secretory, proliferative and apoptotic activities. Distinct expression profiles of two murine cholangiocyte lines, termed small and large have been revealed by microarray analysis. The features of the two cholangiocyte cell lines, categorized partly according to gene ontology, indicate the specific physiological role of each cell line. The large cholangiocytes are characterized as "transport" and "immune/ inflammatory responses". In contrast, small cholangiocytes are associated with properties of limited physiological functional ability and proliferating/migrating potential with specific molecules like Eph receptors, comparable to mesenchymal cells. 'Omic study will be of great help in understanding the heterogeniety of cholangiocytes.

Animals↗
PubMed2004

[Bioinformatics analysis to the differentially expressed genes of normal mucosa and carcinoma of colon].

OBJECTIVE: To systemically analyze the differentially expressed genes from normal mucosa and carcinoma of colon obtained by SSH method. METHODS: An automatic platform for the analysis of nucleotides based on Linux was constructed, and one of the three subtracted libraries from SSH (T -N) was systematically analyzed by this platform. Part of the results was verified by semi- quantity RT-PCR. RESULT: The automatic platform for the analysis of nucleotides based on Linux was successfully constructed. There were 15 contigs from the subtracted T-N libraries, among which 2 had no match with known genes in the GenBank. The expressions of genes Homo Sapiens thymosin beta 4 (THY) and Homo Sapiens HbxAg transactivated protein 2 (XTP) had trends of increase with the progress of normal tissue-adenoma-adenocarcinoma when verified by semi- quantity RT-PCR. CONCLUSION: Linux-based automatic platform provides an efficient way to systematically analyze the nucleotide sequences, which may be used in study on the mechanism of colorectal carcinogenesis.

Colon↗
PubMed2026

Association of MPO Expression with the Immune Microenvironment in Breast Cancer: Insights from Bioinformatics and Single-Cell Analyses.

Breast cancer remains a major cause of cancer-related mortality, and exploratory computational workflows can help prioritize immune-associated markers for further investigation. Here, we used the cancer genome atlas breast invasive carcinoma (TCGA-BRCA) bulk transcriptomic data and the public single-cell dataset GSE161529 to examine associations between myeloperoxidase (MPO) expression, clinical outcomes, immune infiltration, methylation, upstream-regulator annotations, single-cell expression patterns, virtual knockdown sensitivity outputs, drug-gene interaction retrieval, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) annotation. MPO expression was lower in breast cancer tissues than in adjacent non-tumor tissues. Higher MPO expression was associated with a longer progression-free interval, whereas its associations with overall survival and disease-specific survival were not statistically significant. Receiver operating characteristic (ROC) analysis suggested tumor-normal separation within the analyzed public dataset, but this should not be interpreted as clinical diagnostic validation. Immune deconvolution and enrichment analyses indicated that MPO expression mainly tracked with immune- and myeloid-related transcriptional features, rather than establishing tumor-intrinsic regulation of the immune microenvironment. At single-cell resolution, the MPO signal was sparse, with only 85 MPO-positive cells detected before k-nearest neighbor (KNN)-based neighborhood expansion. Detectable MPO signal and MPO-associated scores were interpreted cautiously because they may be influenced by sparse expression, cell-type annotation uncertainty, dropout, doublets, or ambient RNA. In silico virtual knockdown suggested candidate immune- and inflammatory-related transcriptional changes, but these results were considered exploratory and require validation. Drug-gene interaction database (DGIdb)-based drug-gene retrieval and ADMET annotation were used only as preliminary chemical annotations and were not interpreted as therapeutic evidence. Overall, this study provides a reproducible in silico workflow for generating hypotheses about MPO-associated immune/myeloid features in breast cancer, which require external cohort validation and experimental confirmation.

Humans↗
PubMed2026

Human Wings Apart-Like Protein as a Serum Diagnostic Biomarker in Cervical Cancer: An Integrative Bioinformatics Analysis with Serum Validation.

Cervical cancer remains a major threat to women's health worldwide, and reliable serum biomarkers for early detection and therapeutic stratification remain limited. Human wings-apart-like (hWAPL) protein has been implicated in cervical carcinogenesis, but its diagnostic and clinical value has not been fully elucidated. To address this gap, this study integrated public multi-omics datasets, including The Cancer Genome Atlas, GEPIA2, the Human Protein Atlas, and single-cell transcriptomic data, to characterize hWAPL expression, clinicopathological associations, immune infiltration, co-expression networks, post-translational modifications, and drug sensitivity predictions. These findings were evaluated in an independent single-center serum cohort comprising 89 patients with histologically confirmed cervical squamous cell carcinoma and 89 healthy female controls. Serum hWAPL and squamous cell carcinoma antigen (SCC) levels were measured, and diagnostic performance was assessed by receiver operating characteristic curve analysis. In silico, hWAPL was broadly upregulated across multiple malignancies, particularly cervical cancer, enriched in malignant epithelial cells and monocytes/macrophages, and associated with shorter progression-free interval, predicted reduced sensitivity to cisplatin, paclitaxel, and 5-fluorouracil, and predicted sensitivity to MCL-1 and Wee1 inhibitors. In the serum cohort, hWAPL levels were significantly higher in patients than controls and discriminated cervical cancer with an area under the curve of 0.961, exceeding SCC alone. Combining hWAPL with SCC further improved diagnostic performance (area under the curve, 0.974; sensitivity, 93.3%; specificity, 95.5%). These findings suggest that serum hWAPL is a potential novel diagnostic biomarker for cervical squamous cell carcinoma whose performance is enhanced by SCC, whereas the observed associations with chemoresistance and immune microenvironment remodeling are hypothesis-generating and require experimental confirmation.

Humans↗