Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A relative Lempel-Ziv complexity: Application to comparing biological sequences.

ABSTRACT: One of the main tasks in biological sequence analysis is biological sequence comparison. Numerous efficient methods have been developed for sequence comparison. Traditional sequence comparison is based on sequence alignment. In this report, we propose a novel alignment-free method based on the relative Lempel-Ziv complexity to compare biological sequences. The vertebrate transferring genomes and the spike protein sequences are prepared and tested to evaluate the validity of the method. We use this method to build phylogenetic tree of two groups of the sequences. The result demonstrates that our method is powerful and efficient.

SUBMITTER: Liu L

PROVIDER: S-EPMC7094452 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

A relative Lempel-Ziv complexity: Application to comparing biological sequences.

Liu Liwei L Li Dongbo D Bai Fenglan F

Chemical physics letters 20120201

One of the main tasks in biological sequence analysis is biological sequence comparison. Numerous efficient methods have been developed for sequence comparison. Traditional sequence comparison is based on sequence alignment. In this report, we propose a novel alignment-free method based on the relative Lempel-Ziv complexity to compare biological sequences. The vertebrate transferring genomes and the spike protein sequences are prepared and tested to evaluate the validity of the method. We use th ...[more]

PMID: 32226089

Similar Datasets

Propofol anesthesia reduces Lempel-Ziv complexity of spontaneous brain activity in rats.

Project description:Consciousness is thought to scale with brain complexity, and it may be diminished in anesthesia. Lempel-Ziv complexity (LZC) of field potentials has been shown to be a promising measure of the level of consciousness in anesthetized human subjects, neurological patients, and across the sleep-wake states in rats. Whether this relationship holds for intrinsic networks obtained by functional brain imaging has not been tested. To fill this gap of knowledge, we estimated LZC from large-scale dynamic analysis of functional magnetic resonance images (fMRI) in conscious sedated and unconscious anesthetized rats. Blood oxygen dependent (BOLD) signals were obtained from 30-min whole-brain resting-state scans while the anesthetic propofol was infused intravenously at constant infusion rates of 20mg/kg/h (conscious sedated) and 40mg/kg/h (unconscious). Dynamic brain networks were defined at voxel level by sliding window analysis of regional homogeneity (ReHo) of the BOLD signal. From scans performed at low to high propofol dose, the LZC was significantly reduced by 110%. The results suggest that the difference in LZC between conscious sedated and anesthetized unconscious subjects is conserved in rats and this effect is detectable in large-scale brain network obtained from fMRI.

| S-EPMC5086801 | biostudies-other

LZ complexity distance of DNA sequences and its application in phylogenetic tree reconstruction.

Project description:DNA sequences can be treated as finite-length symbol strings over a four-letter alphabet (A, C, T, G). As a universal and computable complexity measure, LZ complexity is valid to describe the complexity of DNA sequences. In this study, a concept of conditional LZ complexity between two sequences is proposed according to the principle of LZ complexity measure. An LZ complexity distance metric between two nonnull sequences is defined by utilizing conditional LZ complexity. Based on LZ complexity distance, a phylogenetic tree of 26 species of placental mammals (Eutheria) with three outgroup species was reconstructed from their complete mitochondrial genomes. On the debate that which two of the three main groups of placental mammals, namely Primates, Ferungulates, and Rodents, are more closely related, the phylogenetic tree reconstructed based on LZ complexity distance supports the suggestion that Primates and Ferungulates are more closely related.

| S-EPMC5172548 | biostudies-literature

Testing robustness of relative complexity measure method constructing robust phylogenetic trees for Galanthus L. using the relative complexity measure.

Project description:BACKGROUND:Most phylogeny analysis methods based on molecular sequences use multiple alignment where the quality of the alignment, which is dependent on the alignment parameters, determines the accuracy of the resulting trees. Different parameter combinations chosen for the multiple alignment may result in different phylogenies. A new non-alignment based approach, Relative Complexity Measure (RCM), has been introduced to tackle this problem and proven to work in fungi and mitochondrial DNA. RESULT:In this work, we present an application of the RCM method to reconstruct robust phylogenetic trees using sequence data for genus Galanthus obtained from different regions in Turkey. Phylogenies have been analyzed using nuclear and chloroplast DNA sequences. Results showed that, the tree obtained from nuclear ribosomal RNA gene sequences was more robust, while the tree obtained from the chloroplast DNA showed a higher degree of variation. CONCLUSIONS:Phylogenies generated by Relative Complexity Measure were found to be robust and results of RCM were more reliable than the compared techniques. Particularly, to overcome MSA-based problems, RCM seems to be a reasonable way and a good alternative to MSA-based phylogenetic analysis. We believe our method will become a mainstream phylogeny construction method especially for the highly variable sequence families where the accuracy of the MSA heavily depends on the alignment parameters.

| S-EPMC3564700 | biostudies-literature

Assessing the low complexity of protein sequences via the low complexity triangle.

Project description:BackgroundProteins with low complexity regions (LCRs) have atypical sequence and structural features. Their amino acid composition varies from the expected, determined proteome-wise, and they do not follow the rules of structural folding that prevail in globular regions. One way to characterize these regions is by assessing the repeatability of a sequence, that is, calculating the local propensity of a region to be part of a repeat.ResultsWe combine two local measures of low complexity, repeatability (using the RES algorithm) and fraction of the most frequent amino acid, to evaluate different proteomes, datasets of protein regions with specific features, and individual cases of proteins with extreme compositions. We apply a representation called 'low complexity triangle' as a proof-of-concept to represent the low complexity measured values. Results show that proteomes have distinct signatures in the low complexity triangle, and that these signatures are associated to complexity features of the sequences. We developed a web tool called LCT (http://cbdm-01.zdv.uni-mainz.de/~munoz/lct/) to allow users to calculate the low complexity triangle of a given protein or region of interest.ConclusionsThe low complexity triangle proves to be a suitable procedure to represent the general low complexity of a sequence or protein dataset. Homorepeats, direpeats, compositionally biased regions and globular regions occupy characteristic positions in the triangle. The described pipeline can be used to characterize LCRs and may help in quantifying the content of degenerated tandem repeats in proteins and proteomes.

| S-EPMC7773278 | biostudies-literature

Protein family expansions and biological complexity.

Project description:During the course of evolution, new proteins are produced very largely as the result of gene duplication, divergence and, in many cases, combination. This means that proteins or protein domains belong to families or, in cases where their relationships can only be recognised on the basis of structure, superfamilies whose members descended from a common ancestor. The size of superfamilies can vary greatly. Also, during the course of evolution organisms of increasing complexity have arisen. In this paper we determine the identity of those superfamilies whose relative sizes in different organisms are highly correlated to the complexity of the organisms. As a measure of the complexity of 38 uni- and multicellular eukaryotes we took the number of different cell types of which they are composed. Of 1,219 superfamilies, there are 194 whose sizes in the 38 organisms are strongly correlated with the number of cell types in the organisms. We give outline descriptions of these superfamilies. Half are involved in extracellular processes or regulation and smaller proportions in other types of activity. Half of all superfamilies have no significant correlation with complexity. We also determined whether the expansions of large superfamilies correlate with each other. We found three large clusters of correlated expansions: one involves expansions in both vertebrates and plants, one just in vertebrates, and one just in plants. Our work identifies important protein families and provides one explanation of the discrepancy between the total number of genes and the apparent physiological complexity of eukaryotic organisms.

| S-EPMC1464810 | biostudies-literature

Hippocampal sequences span experience relative to rewards.

Project description:Hippocampal place cells fire in sequences that span spatial environments and non-spatial modalities, suggesting that hippocampal activity can anchor to the most behaviorally salient aspects of experience. As reward is a highly salient event, we hypothesized that sequences of hippocampal activity can anchor to rewards. To test this, we performed two-photon imaging of hippocampal CA1 neurons as mice navigated virtual environments with changing hidden reward locations. When the reward moved, the firing fields of a subpopulation of cells moved to the same relative position with respect to reward, constructing a sequence of reward-relative cells that spanned the entire task structure. The density of these reward-relative sequences increased with task experience as additional neurons were recruited to the reward-relative population. Conversely, a largely separate subpopulation maintained a spatially-based place code. These findings thus reveal separate hippocampal ensembles can flexibly encode multiple behaviorally salient reference frames, reflecting the structure of the experience.

| S-EPMC10793396 | biostudies-literature

Biological control of appetite: A daunting complexity.

Project description:ObjectiveThis review summarizes a portion of the discussions of an NIH Workshop (Bethesda, MD, 2015) titled "Self-Regulation of Appetite-It's Complicated," which focused on the biological aspects of appetite regulation.MethodsThis review summarizes the key biological inputs of appetite regulation and their implications for body weight regulation.ResultsThese discussions offer an update of the long-held, rigid perspective of an "adipocentric" biological control, taking a broader view that also includes important inputs from the digestive tract, from lean mass, and from the chemical sensory systems underlying taste and smell. It is only beginning to be understood how these biological systems are integrated and how this integrated input influences appetite and food eating behaviors. The relevance of these biological inputs was discussed primarily in the context of obesity and the problem of weight regain, touching on topics related to the biological predisposition for obesity and the impact that obesity treatments (dieting, exercise, bariatric surgery, etc.) might have on appetite and weight loss maintenance. Finally considered is a common theme that pervaded the workshop discussions, which was individual variability.ConclusionsIt is this individual variability in the predisposition for obesity and in the biological response to weight loss that makes the biological component of appetite regulation so complicated. When this individual biological variability is placed in the context of the diverse environmental and behavioral pressures that also influence food eating behaviors, it is easy to appreciate the daunting complexities that arise with the self-regulation of appetite.

| S-EPMC5407690 | biostudies-literature

Ziv-aflibercept in metastatic colorectal cancer.

Project description:The combination of cytotoxic chemotherapy and antiangiogenic agents has become a conventional treatment option for patients with metastatic colorectal cancer. Ziv-aflibercept is a fusion protein which acts as a decoy receptor for vascular endothelial growth factor (VEGF)-A, VEGF-B, and placental growth factor (PlGF); it was approved in combination with 5-fluorouracil, leucovorin, and irinotecan (FOLFIRI) for the treatment of patients with metastatic colorectal cancer that is resistant to or has progressed after an oxaliplatin-containing fluoropyrimidine-based regimen. Herein we review the role of tumor angiogenesis as the rationale for antiangiogenic therapy, the clinical data associated with ziv-aflibercept, and its current role as a treatment option compared to other antiangiogenic agents, such as bevacizumab and regorafenib.

| S-EPMC3869833 | biostudies-literature

Denatured states of low-complexity polypeptide sequences differ dramatically from those of foldable sequences.

Project description:How the primary sequence of a protein encodes conformational preferences that operate early in folding to promote efficient formation of the correct native topology is still poorly understood. To address this issue, we have prepared a set of yeast iso-1-cytochrome c variants that contain polyalanine inserts ranging from 6 to 30 residues in length near the N terminus of the protein. We study the thermodynamics and kinetics of His-heme loop formation in the denatured state at 3 and 6 M guanidine-HCl concentration. We find that polyalanine closely approximates a random coil with excluded volume giving scaling exponents, nu(3), for equilibrium loop formation of 2.26 +/- 0.13 and 1.97 +/- 0.04 in 3 and 6 M guanidine-HCl, respectively. The rate of loop breakage initially decreases and then becomes independent of loop size as would be expected for a random coil. Comparison with previously reported data for denatured state His-heme loop formation for iso-1-cytochrome c and Rhodopseudomonas palustris cytochrome c', shows that foldable sequences deviate significantly from random coil behavior and that the deviation is fold-dependent.

| S-EPMC2895107 | biostudies-literature

Gentle masking of low-complexity sequences improves homology search.

Project description:Detection of sequences that are homologous, i.e. descended from a common ancestor, is a fundamental task in computational biology. This task is confounded by low-complexity tracts (such as atatatatatat), which arise frequently and independently, causing strong similarities that are not homologies. There has been much research on identifying low-complexity tracts, but little research on how to treat them during homology search. We propose to find homologies by aligning sequences with "gentle" masking of low-complexity tracts. Gentle masking means that the match score involving a masked letter is min(0,S), where S is the unmasked score. Gentle masking slightly but noticeably improves the sensitivity of homology search (compared to "harsh" masking), without harming specificity. We show examples in three useful homology search problems: detection of NUMTs (nuclear copies of mitochondrial DNA), recruitment of metagenomic DNA reads to reference genomes, and pseudogene detection. Gentle masking is currently the best way to treat low-complexity tracts during homology search.

| S-EPMC3242753 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data