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At least 919 records · Page 51Linked to original sources
PubMed2026

ReGAIN: a bioinformatics platform for assessing probabilistic co-occurrence between resistance genes in bacterial pathogens.

MOTIVATION: Multidrug-resistant bacterial pathogens continue to rise globally, yet scalable methods are needed to infer how resistance determinants co-occur across pathogen populations and to quantify conditional dependencies underlying co-occurrence and shared genetic context. RESULTS: We present ReGAIN (Resistance Gene Association and Inference Network), an open-source platform that applies Bayesian network structure learning to infer probabilistic, conditional dependency relationships among antibiotic resistance, heavy metal tolerance, stress response, and virulence determinants in bacteria. In contrast to pairwise co-occurrence analyses, ReGAIN reports conditional probabilities, relative risks, and absolute risk differences with confidence intervals to prioritize candidate relationships for downstream prioritization. Applied across ESKAPEE pathogens, ReGAIN recapitulated established resistance gene relationships and identified additional candidate patterns consistent with co-selection and shared genetic context. Together, these results support scalable, reproducible population-wide analysis of resistance networks for surveillance, comparative genomics and epidemiology. AVAILABILITY: ReGAIN analyses are performed using Python v3.11.5 and R v4.4.1 and is available as open-source software through Bioconda at {https://anaconda.org/bioconda/regain-cli}. Source code and documentation can be found at {https://github.com/ERBringHorvath/regain_CLI}. All genomes used in this publication were downloaded from the National Center for Biotechnology Information database. Large supplementary tables and results data from the ESKAPEE pathogen example network analyses can be downloaded from https://figshare.com/articles/dataset/ReGAIN_command_line_software_and_supplemental_figures_/28959431.

Computational Biology↗
PubMed2003

ESTWeb: bioinformatics services for EST sequencing projects.

ESTWeb is an internet based software package designed for uniform data processing and storage for large-scale EST sequencing projects. The package provides for: (a) reception of sequencing chromatograms; (b) sequence processing such as base-calling, vector screening, comparison with public databases; (c) storage of data and analysis in a relational database, (d) generation of a graphical report of individual sequence quality; and (e) issuing of reports with statistics of productivity and redundancy. The software facilitates real-time monitoring and evaluation of EST sequence acquisition progress along an EST sequencing project.

Computational Biology↗
PubMed2003

Markovian negentropies in bioinformatics. 1. A picture of footprints after the interaction of the HIV-1 Psi-RNA packaging region with drugs.

MOTIVATION: Many experts worldwide have highlighted the potential of RNA molecules as drug targets for the chemotherapeutic treatment of a range of diseases. In particular, the molecular pockets of RNA in the HIV-1 packaging region have been postulated as promising sites for antiviral action. The discovery of simpler methods to accurately represent drug-RNA interactions could therefore become an interesting and rapid way to generate models that are complementary to docking-based systems. RESULTS: The entropies of a vibrational Markov chain have been introduced here as physically meaningful descriptors for the local drug-nucleic acid complexes. A study of the interaction of the antibiotic Paromomycin with the packaging region of the RNA present in type-1 HIV has been carried out as an illustrative example of this approach. A linear discriminant function gave rise to excellent discrimination among 80.13% of interacting/non-interacting sites. More specifically, the model classified 36/45 nucleotides (80.0%) that interacted with paromomycin and, in addition, 85/106 (80.2%) footprinted (non-interacting) sites from the RNA viral sequence were recognized. The model showed a high Matthews' regression coefficient (C = 0.64). The Jackknife method was also used to assess the stability and predictability of the model by leaving out adenines, C, G, or U. Matthews' coefficients and overall accuracies for these approaches were between 0.55 and 0.68 and 75.8 and 82.7, respectively. On the other hand, a linear regression model predicted the local binding affinity constants between a specific nucleotide and the aforementioned antibiotic (R2 = 0.83,Q2 = 0.825). These kinds of models may play an important role either in the discovery of new anti-HIV compounds or in the elucidation of their mode of action. AVAILABILITY: On request from the corresponding author (humbertogd@cbq.uclv.edu.cu or humbertogd@navegalia.com).

Binding Sites↗
PubMed2005

TreeScan: a bioinformatic application to search for genotype/phenotype associations using haplotype trees.

SUMMARY: We present the software implementation of the tree scanning method to detect associations between genetic haplotypes and quantitative traits, utilizing the evolutionary history of the haplotypes, in samples of unrelated individuals. AVAILABILITY: The program is available free of charge, under the GNU General Public License. A package including C source code, a Makefile, and Windows (DOS) and Macintosh binaries, can be downloaded from http://darwin.uvigo.es

Chromosome Mapping↗
PubMed2005

Applications of beta-mixture models in bioinformatics.

SUMMARY: We propose a beta-mixture model approach to solve a variety of problems related to correlations of gene-expression levels. For example, in meta-analyses of microarray gene-expression datasets, a threshold value of correlation coefficients for gene-expression levels is used to decide whether gene-expression levels are strongly correlated across studies. Ad hoc threshold values such as 0.5 are often used. In this paper, we use a beta-mixture model approach to divide the correlation coefficients into several populations so that the large correlation coefficients can be identified. Another important application of the proposed method is in finding co-expressed genes. Two examples are provided to illustrate both applications. Through our analysis, we also discover that the popular model selection criteria BIC and AIC are not suitable for the beta-mixture model. To determine the number of components in the mixture model, we suggest an alternative criterion, ICL-BIC, which is shown to perform better in selecting the correct mixture model. SUPPLEMENTARY INFORMATION: http://odin.mdacc.tmc.edu/~yuanj/highcorgeneanno.html.

Animals↗
PubMed2005

Bioinformatics analyses of circular dichroism protein reference databases.

MOTIVATION: Circular dichroism (CD) spectroscopy has become established as a key method for determining the secondary structure contents of proteins which has had a significant impact on molecular biology. Many excellent mathematical protocols have been developed for this purpose and their quality is above question. However, reference database sets of proteins, with CD spectra matched to secondary structure components derived from X-ray structures, provide the key resource for this task. These databases were created many years ago, before most CD spectrophotometers became standardized and before it was commonplace to validate X-ray structures prior to publication. The analyses presented here were undertaken to investigate the overall quality of these reference databases in light of their extensive usage in determining protein secondary structure content from CD spectra. RESULTS: The analyses show that there are a number of significant problems associated with the CD reference database sets in current use. There are disparities between CD spectra for the same protein collected by different groups. These include differences in magnitudes, peak positions or both. However, many current reference sets are now amalgamations of spectra from these groups, introducing inconsistencies that can lead to inaccuracies in the determination of secondary structure components from the CD spectra. A number of the X-ray structures used fall short on the validation criteria now employed as standard for structure determination. Many have substantial percentages of residues in the disallowed regions of the Ramachandran plot. Hence their calculated secondary structure components, used as a foundation for the reference databases, are likely to be in error. Additionally, the coverage of secondary structure space in the reference datasets is poorly correlated to the secondary structure components found in the Protein Data Bank. A conclusion is that a new reference CD database with cross-correlated, machine-independent CD spectra and validated X-ray structures that cover more secondary structure components, including diverse protein folds, is now needed. However, that reasonably accurate values for the secondary structure content of proteins can be determined from spectra is a testament to CD spectroscopy being a very powerful technique.

Circular Dichroism↗
PubMed2005

An attempt to define allergen-specific molecular surface features: a bioinformatic approach.

Allergens are proteins that elicit T helper lymphocyte type 2 (Th2) responses culminating in IgE antibody production and allergic disease. However, we have no answer to the fundamental question of why certain proteins are allergens, while others are not. We hypothesized that analysis of the surface of diverse allergens may reveal common structural features which might enable them to be recognized as Th2-inducing antigens by cells of the innate immune system. We have therefore used the ConSurf server to search for allergen-specific motifs. This has enabled us to identify residue conservation patterns in the homologues of Ara t 8 (plant profilin), Act c 1 (actinidin), Bet v 1 (plant pathogenesis-related protein) and Ves v 5 (venom allergen). The results demonstrate the presence of allergen-specific patches consisting of an unusually high proportion of surface-exposed hydrophobic residues. The patches that have been identified may represent molecular patterns recognizable by cells of the innate immune system.

Algorithms↗
PubMed2004

Bioinformatic identification of polymerizing and transmembrane mucins in the puffer fish Fugu rubripes.

Mucins are large glycoproteins characterized by mucin domains that show little sequence conservation and are rich in the amino acids Ser, Thr, and Pro. To effectively predict mucins from genomic and protein sequences obtained from genome projects, we developed a strategy based on the amino acid compositional bias characteristic of the mucin domains. This strategy is combined with an analysis of other features commonly found in mucins. Our method has now been used to predict mucins in the puffer fish Fugu rubripes that were previously not identified or annotated. At least three gel-forming mucins were found with the same general domain structure as the human MUC2 mucin. In addition one transmembrane mucin was identified with SEA and EGF domains as found in the mammalian transmembrane mucins. These results suggest that the number of gel-forming mucins has been conserved during evolution of the vertebrates, whereas the family of transmembrane mucins has been markedly expanded in the higher vertebrates.

Animals↗
PubMed2002

Ion channels: structural bioinformatics and modelling.

Ion channels are membrane proteins of key physiological and pharmacological importance. As is the case for many integral membrane proteins, X-ray structures are known for a few bacterial channels, yet structures of human homologues are required for analysis of channel-associated diseases and for drug design. Homology modelling can be used to help remedy this deficit. In combination with molecular dynamics simulations and associated calculations, modelling provides a powerful approach to understanding structure/function relationships in human ion channels. Modelling techniques have been applied to two classes of potassium channels: voltage-gated (Kv) and inward rectifier (Kir) channels. Kir channel models, based on the structure of the bacterial channel KcsA, have been used as a starting point for detailed simulation studies that have increased our understanding of ion permeation and selectivity mechanisms. The transmembrane domain of GluR0, a bacterial homologue of mammalian glutamate receptors, also may be modelled using the KcsA structure as a template. Models of the nicotinic acetylcholine receptor may be constructed in a modular fashion. The snail acetylcholine-binding protein provides a template for the extracellular ligand-binding domain. The transmembrane pore region can be modelled on the basis of NMR structures of the pore-lining M2 helix.

Amino Acid Sequence↗
PubMed2003

Elucidation of ataxin-3 and ataxin-7 function by integrative bioinformatics.

The spinocerebellar ataxias (SCAs) are a class of hereditary neurodegenerative diseases, which are caused by the pathological expansion of unstable CAG triplet repeats found in a number of apparently unrelated genes. The proteins encoded by the SCA genes typically translate this expanded (CAG)n repeat into an expanded poly(Q) stretch. Several pathological features are common to all SCAs, irrespective of the gene harbouring the expansion. The specific contributions of the mutated genes are currently hard to assess, as the physiological role of most of the so-called ataxins is not known. By combining the results of profile-based sequence analysis with genome-wide functional data available for model organisms, we have derived detailed predictions of the physiological function of two SCA gene products. Ataxin-3, the protein mutated in Machado Joseph Disease (SCA3), belongs to a novel group of cysteine-proteases and is predicted to be active against ubiquitin chains or related substrates. The catalytic site of this enzyme class is similar to that found in UBP and UCH type ubiquitin proteases. For ataxin-7, the gene product of the SCA7 gene, we have identified an orthology relationship to the yeast open reading frame Ygl066c. Recently published evidence from genome-wide studies suggests that Ygl066c is a component of the SAGA histone acetyltransferase complex. By analogy, a similar role for the mammalian ataxin-7 can be expected. The functional predictions reported here are sufficiently precise to allow a direct experimental verification. Moreover, both findings have implications for the general pathogenesis of spinocerebellar ataxias by providing a direct connection of these diseases with ubiquitin metabolism and histone acetylation.

Acetylation↗