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  1. Article: Physics-Based Signal Analysis of Genome Sequences: An Overview of GenomeBits.

    Canessa, Enrique

    Microorganisms

    2023  Volume 11, Issue 11

    Abstract: A comprehensive overview of the recent physics-inspired genome analysis tool, GenomeBits, is presented. This is based on traditional signal processing methods such as discrete Fourier transform (DFT). GenomeBits can be used to extract underlying genomics ...

    Abstract A comprehensive overview of the recent physics-inspired genome analysis tool, GenomeBits, is presented. This is based on traditional signal processing methods such as discrete Fourier transform (DFT). GenomeBits can be used to extract underlying genomics features from the distribution of nucleotides, and can be further used to analyze the mutation patterns in viral genomes. Examples of the main GenomeBits findings outlining the intrinsic signal organization of genomics sequences for different SARS-CoV-2 variants along the pandemic years 2020-2022 and Monkeypox cases in 2021 are presented to show the usefulness of GenomeBits. GenomeBits results for DFT of SARS-CoV-2 genomes in different geographical regions are discussed, together with the GenomeBits analysis of complete genome sequences for the first coronavirus variants reported: Alpha, Beta, Gamma, Epsilon and Eta. Interesting features of the Delta and Omicron variants in the form of a unique 'order-disorder' transition are uncovered from these samples, as well as from their cumulative distribution function and scatter plots. This class of transitions might reveal the cumulative outcome of mutations on the spike protein. A salient feature of GenomeBits is the mapping of the nucleotide bases (A,T,C,G) into an alternating spin-like numerical sequence via a series having binary (0,1) indicators for each A,T,C,G. This leads to the derivation of a set of statistical distribution curves. Furthermore, the quantum-based extension of the GenomeBits model to an analogous probability measure is shown to identify properties of genome sequences as wavefunctions via a superposition of states. An association of the integral of the GenomeBits coding and a binding-like energy can, in principle, also be established. The relevance of these different results in bioinformatics is analyzed.
    Language English
    Publishing date 2023-11-09
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2720891-6
    ISSN 2076-2607
    ISSN 2076-2607
    DOI 10.3390/microorganisms11112733
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: GenomeBits Characterization of MPXV.

    Canessa, Enrique

    Genes

    2022  Volume 13, Issue 12

    Abstract: Genome sequences of the monkeypox virus (MPXV) causing the current outbreak are being reported from an increasing number of countries. We present a letter-to-numerical sequence study via GenomeBits signal mapping in order to characterize the evolution of ...

    Abstract Genome sequences of the monkeypox virus (MPXV) causing the current outbreak are being reported from an increasing number of countries. We present a letter-to-numerical sequence study via GenomeBits signal mapping in order to characterize the evolution of the MPXV via simple statistical analysis. Histograms, empirical and theoretical cumulative distribution curves and the resulting scatter plots for the base nucleotides A and C versus their complementary base nucleotides T and G are discussed. GenomeBits may help the surveillance of emergent infectious diseases.
    MeSH term(s) Humans ; Monkeypox virus/genetics ; Mpox (monkeypox) ; DNA, Viral/genetics
    Chemical Substances DNA, Viral
    Language English
    Publishing date 2022-11-27
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2527218-4
    ISSN 2073-4425 ; 2073-4425
    ISSN (online) 2073-4425
    ISSN 2073-4425
    DOI 10.3390/genes13122223
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Wave-like behaviour in (0,1) binary sequences.

    Canessa, Enrique

    Scientific reports

    2022  Volume 12, Issue 1, Page(s) 13971

    Abstract: A comprehensive study of the properties of finite (0,1) binary systems from the mathematical viewpoint of quantum theory is presented. This is a quantum-inspired extension of the GenomeBits model to characterize observed genome sequences, where a complex ...

    Abstract A comprehensive study of the properties of finite (0,1) binary systems from the mathematical viewpoint of quantum theory is presented. This is a quantum-inspired extension of the GenomeBits model to characterize observed genome sequences, where a complex wavefunction [Formula: see text] is considered as an analogous probability measure and it is related to an alternating (0,1) binary series having independent distributed terms. The real and imaginary spectrum of [Formula: see text] vs. the nucleotide base positions display characteristic features of sound waves. This approach represents a novel perspective for identifying and "observing" emergent properties of genome sequences in the form of wavefunctions via superposition states. The motivation is to develop a simple algorithm to perform wave calculations from binary sequences and to apply these wave functions to sonification.
    MeSH term(s) Algorithms ; Genome ; Quantum Theory
    Language English
    Publishing date 2022-08-17
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-022-18360-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Uncovering Signals from the Coronavirus Genome.

    Canessa, Enrique

    Genes

    2021  Volume 12, Issue 7

    Abstract: A signal analysis of the complete genome sequenced for coronavirus variants of concern-B.1.1.7 (Alpha), B.1.135 (Beta) and P1 (Gamma)-and coronavirus variants of interest-B.1.429-B.1.427 (Epsilon) and B.1.525 (Eta)-is presented using open GISAID data. We ...

    Abstract A signal analysis of the complete genome sequenced for coronavirus variants of concern-B.1.1.7 (Alpha), B.1.135 (Beta) and P1 (Gamma)-and coronavirus variants of interest-B.1.429-B.1.427 (Epsilon) and B.1.525 (Eta)-is presented using open GISAID data. We deal with a certain new type of finite alternating sum series having independently distributed terms associated with binary (0,1) indicators for the nucleotide bases. Our method provides additional information to conventional similarity comparisons via alignment methods and Fourier Power Spectrum approaches. It leads to uncover distinctive patterns regarding the intrinsic data organization of complete genomics sequences according to its progression along the nucleotide bases position. The present new method could be useful for the bioinformatics surveillance and dynamics of coronavirus genome variants.
    MeSH term(s) Computational Biology/methods ; Coronavirus/genetics ; Genome, Viral ; Humans ; SARS-CoV-2/genetics ; SARS-CoV-2/isolation & purification ; Viral Proteins/genetics
    Chemical Substances Viral Proteins
    Language English
    Publishing date 2021-06-25
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2527218-4
    ISSN 2073-4425 ; 2073-4425
    ISSN (online) 2073-4425
    ISSN 2073-4425
    DOI 10.3390/genes12070973
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: GenomeBits Characterization of MPXV

    Canessa, Enrique

    Genes (Basel). 2022 Nov. 27, v. 13, no. 12

    2022  

    Abstract: Genome sequences of the monkeypox virus (MPXV) causing the current outbreak are being reported from an increasing number of countries. We present a letter-to-numerical sequence study via GenomeBits signal mapping in order to characterize the evolution of ...

    Abstract Genome sequences of the monkeypox virus (MPXV) causing the current outbreak are being reported from an increasing number of countries. We present a letter-to-numerical sequence study via GenomeBits signal mapping in order to characterize the evolution of the MPXV via simple statistical analysis. Histograms, empirical and theoretical cumulative distribution curves and the resulting scatter plots for the base nucleotides A and C versus their complementary base nucleotides T and G are discussed. GenomeBits may help the surveillance of emergent infectious diseases.
    Keywords Monkeypox virus ; cumulative distribution ; evolution ; genome ; monitoring ; nucleotides
    Language English
    Dates of publication 2022-1127
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article ; Online
    ZDB-ID 2527218-4
    ISSN 2073-4425
    ISSN 2073-4425
    DOI 10.3390/genes13122223
    Database NAL-Catalogue (AGRICOLA)

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  6. Article: Uncovering Signals from the Coronavirus Genome

    Canessa, Enrique

    Genes. 2021 June 25, v. 12, no. 7

    2021  

    Abstract: A signal analysis of the complete genome sequenced for coronavirus variants of concern—B.1.1.7 (Alpha), B.1.135 (Beta) and P1 (Gamma)—and coronavirus variants of interest—B.1.429–B.1.427 (Epsilon) and B.1.525 (Eta)—is presented using open GISAID data. We ...

    Abstract A signal analysis of the complete genome sequenced for coronavirus variants of concern—B.1.1.7 (Alpha), B.1.135 (Beta) and P1 (Gamma)—and coronavirus variants of interest—B.1.429–B.1.427 (Epsilon) and B.1.525 (Eta)—is presented using open GISAID data. We deal with a certain new type of finite alternating sum series having independently distributed terms associated with binary (0,1) indicators for the nucleotide bases. Our method provides additional information to conventional similarity comparisons via alignment methods and Fourier Power Spectrum approaches. It leads to uncover distinctive patterns regarding the intrinsic data organization of complete genomics sequences according to its progression along the nucleotide bases position. The present new method could be useful for the bioinformatics surveillance and dynamics of coronavirus genome variants.
    Keywords Orthocoronavirinae ; bioinformatics ; genomics ; monitoring
    Language English
    Dates of publication 2021-0625
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article
    ZDB-ID 2527218-4
    ISSN 2073-4425
    ISSN 2073-4425
    DOI 10.3390/genes12070973
    Database NAL-Catalogue (AGRICOLA)

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  7. Article ; Online: GenomeBits insight into omicron and delta variants of coronavirus pathogen.

    Canessa, Enrique / Tenze, Livio

    PloS one

    2022  Volume 17, Issue 7, Page(s) e0271039

    Abstract: We apply the new GenomeBits method to uncover underlying genomic features of omicron and delta coronavirus variants. This is a statistical algorithm whose salient feature is to map the nucleotide bases into a finite alternating (±) sum series of ... ...

    Abstract We apply the new GenomeBits method to uncover underlying genomic features of omicron and delta coronavirus variants. This is a statistical algorithm whose salient feature is to map the nucleotide bases into a finite alternating (±) sum series of distributed terms of binary (0,1) indicators. We show how by this method, distinctive signals can be uncovered out of the intrinsic data organization of amino acid progressions along their base positions. Results reveal a sort of 'ordered' (or constant) to 'disordered' (or peaked) transition around the coronavirus S-spike protein region. Together with our previous results for past variants of coronavirus: Alpha, Beta, Gamma, Epsilon and Eta, we conclude that the mapping into GenomeBits strands of omicron and delta variants can help to characterize mutant pathogens.
    MeSH term(s) Coronavirus/genetics ; Spike Glycoprotein, Coronavirus/genetics
    Chemical Substances Spike Glycoprotein, Coronavirus
    Language English
    Publishing date 2022-07-11
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0271039
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Describing and understanding the time course of the property listing task.

    Canessa, Enrique / Chaigneau, Sergio E / Moreno, Sebastián

    Cognitive processing

    2023  Volume 25, Issue 1, Page(s) 61–74

    Abstract: To study linguistically coded concepts, researchers often resort to the Property Listing Task (PLT). In a PLT, participants are asked to list properties that describe a concept (e.g., for DOG, subjects may list "is a pet", "has four legs", etc.). When ... ...

    Abstract To study linguistically coded concepts, researchers often resort to the Property Listing Task (PLT). In a PLT, participants are asked to list properties that describe a concept (e.g., for DOG, subjects may list "is a pet", "has four legs", etc.). When PLT data is collected for many concepts, researchers obtain Conceptual Properties Norms (CPNs), which are used to study semantic content and as a source of control variables. Though the PLT and CPNs are widely used across psychology, only recently a model that describes the listing course of a PLT has been developed and validated. That original model describes the listing course using order of production of properties. Here we go a step beyond and validate the model using response times (RT), i.e., the time from cue onset to property listing. Our results show that RT data exhibits the same regularities observed in the previous model, but now we can also analyze the time course, i.e., dynamics of the PLT. As such, the RT validated model may be applied to study several similar memory retrieval tasks, such as the Free Listing Task, Verbal Fluidity Task, and to research related cognitive processes. To illustrate those kinds of analyses, we present a brief example of the difference in PLT's dynamics between listing properties for abstract versus concrete concepts, which shows that the model may be fruitfully applied to study concepts.
    MeSH term(s) Humans ; Semantics ; Memory ; Reaction Time
    Language English
    Publishing date 2023-09-16
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 2075054-7
    ISSN 1612-4790 ; 1612-4782
    ISSN (online) 1612-4790
    ISSN 1612-4782
    DOI 10.1007/s10339-023-01160-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: GenomeBits insight into omicron and delta variants of coronavirus pathogen

    Canessa, Enrique / Tenze, Livio

    bioRxiv

    Abstract: Differences and correspondence regarding the intrinsic data organisation of complete delta and omicron genome sequences according to its progression along the nucleotide A,C,G,T bases position are analysed. We found a sort of 9ordered9 to 9disordered9 ... ...

    Abstract Differences and correspondence regarding the intrinsic data organisation of complete delta and omicron genome sequences according to its progression along the nucleotide A,C,G,T bases position are analysed. We found a sort of 9ordered9 to 9disordered9 transition around the S-spike protein region in the curves obtained from finite alternating sum series having independently distributed terms associated with (0,1) binary indicators for the nucleotides. To uncover such underlying features of genome sequences may assist in the development of synthetic proteins.
    Keywords covid19
    Language English
    Publishing date 2022-01-12
    Publisher Cold Spring Harbor Laboratory
    Document type Article ; Online
    DOI 10.1101/2022.01.11.475877
    Database COVID19

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  10. Article ; Online: Using agreement probability to study differences in types of concepts and conceptualizers.

    Canessa, Enrique / Chaigneau, Sergio E / Moreno, Sebastián

    Behavior research methods

    2022  Volume 56, Issue 1, Page(s) 93–112

    Abstract: Agreement probability p(a) is a homogeneity measure of lists of properties produced by participants in a Property Listing Task (PLT) for a concept. Agreement probability's mathematical properties allow a rich analysis of property-based descriptions. To ... ...

    Abstract Agreement probability p(a) is a homogeneity measure of lists of properties produced by participants in a Property Listing Task (PLT) for a concept. Agreement probability's mathematical properties allow a rich analysis of property-based descriptions. To illustrate, we use p(a) to delve into the differences between concrete and abstract concepts in sighted and blind populations. Results show that concrete concepts are more homogeneous within sighted and blind groups than abstract ones (i.e., exhibit a higher p(a) than abstract ones) and that concrete concepts in the blind group are less homogeneous than in the sighted sample. This supports the idea that listed properties for concrete concepts should be more similar across subjects due to the influence of visual/perceptual information on the learning process. In contrast, abstract concepts are learned based mainly on social and linguistic information, which exhibit more variability among people, thus, making the listed properties more dissimilar across subjects. Relative to abstract concepts, the difference in p(a) between sighted and blind is not statistically significant. Though this is a null result, and should be considered with care, it is expected because abstract concepts should be learned by paying attention to the same social and linguistic input in both, blind and sighted, and thus, there is no reason to expect that the respective lists of properties should differ. Finally, we used p(a) to classify concrete and abstract concepts with a good level of certainty. All these analyses suggest that p(a) can be fruitfully used to study data obtained in a PLT.
    MeSH term(s) Humans ; Learning ; Concept Formation ; Blindness
    Language English
    Publishing date 2022-12-05
    Publishing country United States
    Document type Journal Article
    ZDB-ID 231560-9
    ISSN 1554-3528 ; 0743-3808 ; 1554-351X
    ISSN (online) 1554-3528
    ISSN 0743-3808 ; 1554-351X
    DOI 10.3758/s13428-022-02030-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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