Data Compression Concepts and Algorithms and Their Applications to Bioinformatics

Data compression at its base is concerned with how information is organized in data. Understanding this organization can lead to efficient ways of representing the information and hence data compression. In this paper we review the ways in which ideas and approaches fundamental to the theory and practice of data compression have been used in the area of bioinformatics. We look at how basic theoretical ideas from data compression, such as the notions of entropy, mutual information, and complexity have been used for analyzing biological sequences in order to discover hidden patterns, infer phylogenetic relationships between organisms and study viral populations. Finally, we look at how inferred grammars for biological sequences have been used to uncover structure in biological sequences

Criminal Law--Kidnaping--Detention Incidental to Crime of Robbery Held Not Kidnaping (People v. Levy, 15 N.Y.2d 159 (1965))

Data compression at its base is concerned with how information is organized in data. Understanding this organization can lead to efficient ways of representing the information and hence data compression. In this paper we review the ways in which ideas and approaches fundamental to the theory and practice of data compression have been used in the area of bioinformatics. We look at how basic theoretical ideas from data compression, such as the notions of entropy, mutual information, and complexity have been used for analyzing biological sequences in order to discover hidden patterns, infer phylogenetic relationships between organisms and study viral populations. Finally, we look at how inferred grammars for biological sequences have been used to uncover structure in biological sequences

Data Compression Concepts and Algorithms and Their Applications to Bioinformatics

Data compression at its base is concerned with how information is organized in data. Understanding this organization can lead to efficient ways of representing the information and hence data compression. In this paper we review the ways in which ideas and approaches fundamental to the theory and practice of data compression have been used in the area of bioinformatics. We look at how basic theoretical ideas from data compression, such as the notions of entropy, mutual information, and complexity have been used for analyzing biological sequences in order to discover hidden patterns, infer phylogenetic relationships between organisms and study viral populations. Finally, we look at how inferred grammars for biological sequences have been used to uncover structure in biological sequences

PEGylated calix[4]arene as a carrier for a Bodipy-based photosensitizer

Cataloged from PDF version of article.Heavy atom substituted Bodipy compounds, unlike the parent chromophore, undergo rapid intersystem crossing to generate singlet oxygen, which is the primary cytotoxic agent exploited in PDT. In this work, we show that an organic soluble calix[4]arene can be functionalized by Knoevenagel reaction and then converted into an amphiphilic photosensitizer in a few steps. In addition to generating a potentially useful photosensitizer, the sequence of reactions is the first use of a Bodipy dye as a chromophoric/fluorogenic label without the typical reactive functional groups. 2013 Elsevier Ltd. All rights reserved

Magnetic resonance imaging findings in 46 elbows with a radial head fracture

Radial head fractures are common, and may be associated with other injuries of clinical importance. We present the results of a standard additional MRI scan for patients with a radial head fracture. PATIENTS AND METhods: 44 patients (mean age 47 years) with 46 radial head fractures underwent MRI. 17 elbows had a Mason type-I fracture, 23 a Mason type-II fracture, and 6 elbows had a Mason type-III fracture. Associated injuries were found in 35 elbows: 28 elbows had a lateral collateral ligament lesion, 18 had capitellar injury, 1 had a coronoid fracture, and 1 elbow had medial collateral ligament injury. The incidence of associated injuries with radial head fractures found with MRI was high. The clinical relevance should be investigate

RAIphy: Phylogenetic classification of metagenomics samples using iterative refinement of relative abundance index profiles

Background: Computational analysis of metagenomes requires the taxonomical assignment of the genome contigs assembled from DNA reads of environmental samples. Because of the diverse nature of microbiomes, the length of the assemblies obtained can vary between a few hundred bp to a few hundred Kbp. Current taxonomic classification algorithms provide accurate classification for long contigs or for short fragments from organisms that have close relatives with annotated genomes. These are significant limitations for metagenome analysis because of the complexity of microbiomes and the paucity of existing annotated genomes. Results: We propose a robust taxonomic classification method, RAIphy, that uses a novel sequence similarity metric with iterative refinement of taxonomic models and functions effectively without these limitations. We have tested RAIphy with synthetic metagenomics data ranging between 100 bp to 50 Kbp. Within a sequence read range of 100 bp-1000 bp, the sensitivity of RAIphy ranges between 38%-81% outperforming the currently popular composition-based methods for reads in this range. Comparison with computationally more intensive sequence similarity methods shows that RAIphy performs competitively while being significantly faster. The sensitivityspecificity characteristics for relatively longer contigs were compared with the PhyloPythia and TACOA algorithms. RAIphy performs better than these algorithms at varying clade-levels. For an acid mine drainage (AMD) metagenome, RAIphy was able to taxonomically bin the sequence read set more accurately than the currently available methods, Phymm and MEGAN, and more accurately in two out of three tests than the much more computationally intensive method, PhymmBL. Conclusions: With the introduction of the relative abundance index metric and an iterative classification method, we propose a taxonomic classification algorithm that performs competitively for a large range of DNA contig lengths assembled from metagenome data. Because of its speed, simplicity, and accuracy RAIphy can be successfully used in the binning process for a broad range of metagenomic data obtained from environmental samples

Multiple Phenotypes in Adult Mice following Inactivation of the Coxsackievirus and Adenovirus Receptor (Car) Gene

To determine the normal function of the Coxsackievirus and Adenovirus Receptor (CAR), a protein found in tight junctions and other intercellular complexes, we constructed a mouse line in which the CAR gene could be disrupted at any chosen time point in a broad spectrum of cell types and tissues. All knockouts examined displayed a dilated intestinal tract and atrophy of the exocrine pancreas with appearance of tubular complexes characteristic of acinar-to-ductal metaplasia. The mice also exhibited a complete atrio-ventricular block and abnormal thymopoiesis. These results demonstrate that CAR exerts important functions in the physiology of several organs in vivo

Metabolic response to a ketogenic breakfast in the healthy elderly.

OBJECTIVE: To determine whether the metabolism of glucose or ketones differs in the healthy elderly compared to young or middle-aged adults during mild, short-term ketosis induced by a ketogenic breakfast. DESIGN AND PARTICIPANTS: Healthy subjects in three age groups (23 +/- 1, 50 +/- 1 and 76 +/- 2 y old) were given a ketogenic meal and plasma beta -hydroxybutyrate, glucose, insulin, triacylglycerols, total cholesterol, non-esterified fatty acids and breath acetone were measured over the subsequent 6 h. Each subject completed the protocol twice in order to determine the oxidation of a tracer dose of both carbon-13 (13C) glucose and 13C-beta-hydroxybutyrate. The tracers were given separately in random order. Apolipoprotein E genotype was also determined in all subjects. RESULTS: Plasma glucose decreased and beta-hydroxybutyrate, acetone and insulin increased similarly over 6 h in all three groups after the ketogenic meal. There was no significant change in cholesterol, triacylglycerols or non-esterified fatty acids over the 6 h. 13C-glucose and 13C-beta-hydroxybutyrate oxidation peaked at 2-3 h postdose for all age groups. Cumulative 13C-glucose oxidation over 24 h was significantly higher in the elderly but only versus the middle-aged group. There was no difference in cumulative 13C-beta-hydroxybutyrate oxidation between the three groups. Apolipoprotein E (epsilon 4) was associated with elevated fasting cholesterol but was unrelated to the other plasma metabolites. CONCLUSION: Elderly people in relatively good health have a similar capacity to produce ketones and to oxidize 13C-beta-hydroxybutyrate as middle-aged or young adults, but oxidize 13C-glucose a little more rapidly than healthy middle-aged adult

Alzheimer disease models and human neuropathology: similarities and differences

Animal models aim to replicate the symptoms, the lesions or the cause(s) of Alzheimer disease. Numerous mouse transgenic lines have now succeeded in partially reproducing its lesions: the extracellular deposits of Aβ peptide and the intracellular accumulation of tau protein. Mutated human APP transgenes result in the deposition of Aβ peptide, similar but not identical to the Aβ peptide of human senile plaque. Amyloid angiopathy is common. Besides the deposition of Aβ, axon dystrophy and alteration of dendrites have been observed. All of the mutations cause an increase in Aβ 42 levels, except for the Arctic mutation, which alters the Aβ sequence itself. Overexpressing wild-type APP alone (as in the murine models of human trisomy 21) causes no Aβ deposition in most mouse lines. Doubly (APP × mutated PS1) transgenic mice develop the lesions earlier. Transgenic mice in which BACE1 has been knocked out or overexpressed have been produced, as well as lines with altered expression of neprilysin, the main degrading enzyme of Aβ. The APP transgenic mice have raised new questions concerning the mechanisms of neuronal loss, the accumulation of Aβ in the cell body of the neurons, inflammation and gliosis, and the dendritic alterations. They have allowed some insight to be gained into the kinetics of the changes. The connection between the symptoms, the lesions and the increase in Aβ oligomers has been found to be difficult to unravel. Neurofibrillary tangles are only found in mouse lines that overexpress mutated tau or human tau on a murine tau −/− background. A triply transgenic model (mutated APP, PS1 and tau) recapitulates the alterations seen in AD but its physiological relevance may be discussed. A number of modulators of Aβ or of tau accumulation have been tested. A transgenic model may be analyzed at three levels at least (symptoms, lesions, cause of the disease), and a reading key is proposed to summarize this analysis

COMPUTATIONAL GENOMIC SIGNATURES AND METAGENOMICS

Mathematical characterizations of biological sequences form one of the main elements of bioinformatics. In this work, a class of DNA sequence characterization, namely computational genomics signatures, which capture global features of these sequences is used to address emerging computational biology challenges. Because of the species specificity and pervasiveness of genome signatures, it is possible to use these signatures to characterize and identify a genome or a taxonomic unit using a short genome fragment from that source. However, the identification accuracy is generally poor when the sequence model and the sequence distance measure are not selected carefully. We show that the use of relative distance measures instead of absolute metrics makes it possible to obtain better detection accuracy. Furthermore, the use of relative metrics can create opportunities for using more complex models to develop genome signatures, which cannot be used efficiently when conventional distance measures are used. Using a relative distance measure and a model based on the relative abundance of oligonucleotides in a genome fragment, a novel genome signature was defined. This signature was employed to address a class of metagenomics problems. The metagenomics approach enables sampling and sequencing of a microbial community without isolating and culturing single species. Determining the taxonomic classification of the bacterial species within the microbial community from the mixture of short DNA fragments is a difficult computational challenge. We present supervised and unsupervised algorithms for taxonomic classification of metagenomics data and demonstrate their effectiveness on simulated and real-world data. The supervised algorithm, RAIphy, classifies metagenome fragments of unknown origin by assigning them to the taxa, defined in a signature database of previously sequenced microbial genomes. The signatures in the database are updated iteratively during the classification process. Most metagenomics samples include unidentified species, thus they require clustering. Pseudo-assembly of fragments, followed by clustering of taxa is employed in the unsupervised setting. The signatures developed in this work are more specific-specific and pervasive than any signatures currently available in the literature, and demonstrate the potential and viability of using genome signatures to solve various metagenomics problems as well as other challenges in computational biology