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  1. Book ; Online: Intelligent Systems for Genome Functional Annotations

    Ahmad, Shandar / Fernandez, Michael / Ballester, Pedro

    2020  

    Keywords Science: general issues ; Medical genetics ; functional annotation ; protein-protein interaction (PPI) ; machine learning ; gene annotation ; intelligent system applications
    Size 1 electronic resource (103 pages)
    Publisher Frontiers Media SA
    Document type Book ; Online
    Note English ; Open Access
    HBZ-ID HT021230912
    ISBN 9782889660902 ; 2889660907
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article ; Online: Potential of age distribution profiles for the prediction of COVID-19 infection origin in a patient group

    Shandar Ahmad

    Informatics in Medicine Unlocked, Vol 20, Iss , Pp 100364- (2020)

    2020  

    Abstract: The COVID-19 pandemic is a serious and global public health concern. It is now well known that COVID-19 cases may result in mild symptoms leading to patient recovery. However, severity of infection, fatality rates, and treatment responses across ... ...

    Abstract The COVID-19 pandemic is a serious and global public health concern. It is now well known that COVID-19 cases may result in mild symptoms leading to patient recovery. However, severity of infection, fatality rates, and treatment responses across different countries, age groups, and demographic groups suggest that the nature of infection is diverse, and a timely investigation of the same is needed for evolving sound treatment and preventive strategies. This paper reports an the analysis of age distribution patterns in six groups of Indian COVID-19 patient populations based on their likely geographical origin of infection viz. the United Kingdom, North America, the European Union, the Middle East, and Asian countries. It was observed that patient groups stratified in this way had a distinct age profile and that some of these groups e.g. patient groups from Asia, the European Union, and the United Kingdom formed a different cluster than those from North America, the Middle East, and other regions. Patient age profiles of a population were found to be highly predictive of the group they belong to, and there are indications of their distinct recovery and fatality rates across gender. Altogether this study provides a scalable framework to estimate the source of infection in a new population of COVID-19 patients with unknown origin. It is also concluded that greater public availability of age and other demographic profile details of patients may be helpful in gaining robust insights into COVID-19 infection origins. Datasets and scripts used in this work are shared at http://covid.sciwhylab.org.
    Keywords COVID-19 ; Age profiles ; Pandemic analysis ; Origin of infection ; Fatality ; Computer applications to medicine. Medical informatics ; R858-859.7 ; covid19
    Language English
    Publishing date 2020-01-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article: Potential of age distribution profiles for the prediction of COVID-19 infection origin in a patient group.

    Ahmad, Shandar

    Informatics in medicine unlocked

    2020  Volume 20, Page(s) 100364

    Abstract: The COVID-19 pandemic is a serious and global public health concern. It is now well known that COVID-19 cases may result in mild symptoms leading to patient recovery. However, severity of infection, fatality rates, and treatment responses across ... ...

    Abstract The COVID-19 pandemic is a serious and global public health concern. It is now well known that COVID-19 cases may result in mild symptoms leading to patient recovery. However, severity of infection, fatality rates, and treatment responses across different countries, age groups, and demographic groups suggest that the nature of infection is diverse, and a timely investigation of the same is needed for evolving sound treatment and preventive strategies. This paper reports an the analysis of age distribution patterns in six groups of Indian COVID-19 patient populations based on their likely geographical origin of infection viz. the United Kingdom, North America, the European Union, the Middle East, and Asian countries. It was observed that patient groups stratified in this way had a distinct age profile and that some of these groups e.g. patient groups from Asia, the European Union, and the United Kingdom formed a different cluster than those from North America, the Middle East, and other regions. Patient age profiles of a population were found to be highly predictive of the group they belong to, and there are indications of their distinct recovery and fatality rates across gender. Altogether this study provides a scalable framework to estimate the source of infection in a new population of COVID-19 patients with unknown origin. It is also concluded that greater public availability of age and other demographic profile details of patients may be helpful in gaining robust insights into COVID-19 infection origins. Datasets and scripts used in this work are shared at http://covid.sciwhylab.org.
    Keywords covid19
    Language English
    Publishing date 2020-06-04
    Publishing country England
    Document type Journal Article
    ISSN 2352-9148
    ISSN 2352-9148
    DOI 10.1016/j.imu.2020.100364
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Potential of age distribution profiles for the prediction of COVID-19 infection origin in a patient group

    Ahmad, Shandar

    Informatics in Medicine Unlocked

    2020  Volume 20, Page(s) 100364

    Keywords covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    ISSN 2352-9148
    DOI 10.1016/j.imu.2020.100364
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Analysis and Prediction of Pathogen Nucleic Acid Specificity for Toll-like Receptors in Vertebrates.

    Jain, Anuja / Begum, Tina / Ahmad, Shandar

    Journal of molecular biology

    2023  Volume 435, Issue 17, Page(s) 168208

    Abstract: Identification of key sequence, expression and function related features of nucleic acid-sensing host proteins is of fundamental importance to understand the dynamics of pathogen-specific host responses. To meet this objective, we considered toll-like ... ...

    Abstract Identification of key sequence, expression and function related features of nucleic acid-sensing host proteins is of fundamental importance to understand the dynamics of pathogen-specific host responses. To meet this objective, we considered toll-like receptors (TLRs), a representative class of membrane-bound sensor proteins, from 17 vertebrate species covering mammals, birds, reptiles, amphibians, and fishes in this comparative study. We identified the molecular signatures of host TLRs that are responsible for sensing pathogen nucleic acids or other pathogen-associated molecular patterns (PAMPs), and potentially play important roles in host defence mechanism. Interestingly, our findings reveal that such host-specific features are directly related to the strand (single or double) specificity of nucleic acid from pathogens. However, during host-pathogen interactions, such features were unable to explain the pathogenic PAMP (i.e., DNA, RNA or other) selectivity, suggesting a more complex mechanism. Using these features, we developed a number of machine learning models, of which Random Forest achieved a high performance (94.57% accuracy) to predict strand specificity of TLRs from protein-derived features. We applied the trained model to propose strand specificity of some previously uncharacterized distinct fish-specific novel TLRs (TLR18, TLR23, TLR24, TLR25, TLR27).
    MeSH term(s) Animals ; Evolution, Molecular ; Fishes ; Immunity, Innate ; Mammals/genetics ; Nucleic Acids/chemistry ; Phylogeny ; Toll-Like Receptors/chemistry ; Toll-Like Receptors/genetics ; Vertebrates/genetics ; Vertebrates/immunology ; Substrate Specificity ; Host-Pathogen Interactions/immunology
    Chemical Substances Nucleic Acids ; Toll-Like Receptors
    Language English
    Publishing date 2023-07-20
    Publishing country Netherlands
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 80229-3
    ISSN 1089-8638 ; 0022-2836
    ISSN (online) 1089-8638
    ISSN 0022-2836
    DOI 10.1016/j.jmb.2023.168208
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 867: Show issues Location:
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    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  6. Article: Potential of age distribution profiles for the prediction of COVID-19 infection origin in a patient group

    Ahmad, Shandar

    Inform. Med. Unlocked

    Abstract: The COVID-19 pandemic is a serious and global public health concern. It is now well known that COVID-19 cases may result in mild symptoms leading to patient recovery. However, severity of infection, fatality rates, and treatment responses across ... ...

    Abstract The COVID-19 pandemic is a serious and global public health concern. It is now well known that COVID-19 cases may result in mild symptoms leading to patient recovery. However, severity of infection, fatality rates, and treatment responses across different countries, age groups, and demographic groups suggest that the nature of infection is diverse, and a timely investigation of the same is needed for evolving sound treatment and preventive strategies. This paper reports an the analysis of age distribution patterns in six groups of Indian COVID-19 patient populations based on their likely geographical origin of infection viz. the United Kingdom, North America, the European Union, the Middle East, and Asian countries. It was observed that patient groups stratified in this way had a distinct age profile and that some of these groups e.g. patient groups from Asia, the European Union, and the United Kingdom formed a different cluster than those from North America, the Middle East, and other regions. Patient age profiles of a population were found to be highly predictive of the group they belong to, and there are indications of their distinct recovery and fatality rates across gender. Altogether this study provides a scalable framework to estimate the source of infection in a new population of COVID-19 patients with unknown origin. It is also concluded that greater public availability of age and other demographic profile details of patients may be helpful in gaining robust insights into COVID-19 infection origins. Datasets and scripts used in this work are shared at http://covid.sciwhylab.org.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #526602
    Database COVID19

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  7. Article ; Online: Analysis and prediction of pathogen nucleic acid specificity for toll-like receptors in vertebrates

    Jain, Anuja / Begum, Tina / Ahmad, Shandar

    Journal of Molecular Biology. 2023, p.168208-

    2023  , Page(s) 168208–

    Abstract: Identification of key sequence, expression and function related features of nucleic acid-sensing host proteins is of fundamental importance to understand the dynamics of pathogen-specific host responses. To meet this objective, we considered toll-like ... ...

    Abstract Identification of key sequence, expression and function related features of nucleic acid-sensing host proteins is of fundamental importance to understand the dynamics of pathogen-specific host responses. To meet this objective, we considered toll-like receptors (TLRs), a representative class of membrane-bound sensor proteins, from 17 vertebrate species covering mammals, birds, reptiles, amphibians, and fishes in this comparative study. We identified the molecular signatures of host TLRs that are responsible for sensing pathogen nucleic acids or other pathogen-associated molecular patterns (PAMPs), and potentially play important roles in host defence mechanism. Interestingly, our findings reveal that such host-specific features are directly related to the strand (single or double) specificity of nucleic acid from pathogens. However, during host-pathogen interactions, such features were unable to explain the pathogenic PAMP (i.e., DNA, RNA or other) selectivity, suggesting a more complex mechanism. Using these features, we developed a number of machine learning models, of which Random Forest achieved a high performance (94.57% accuracy) to predict strand specificity of TLRs from protein-derived features. We applied the trained model to propose strand specificity of some previously uncharacterized distinct fish-specific novel TLRs (TLR18, TLR23, TLR24, TLR25, TLR27).
    Keywords DNA ; RNA ; comparative study ; host specificity ; models ; molecular biology ; pathogens ; prediction ; vertebrates ; Toll-like receptors ; Leucine-Rich-Repeats ; Gene expression ; Gene age ; Machine learning approach ; Random forest
    Language English
    Publishing place Elsevier Ltd
    Document type Article ; Online
    Note Pre-press version
    ZDB-ID 80229-3
    ISSN 1089-8638 ; 0022-2836
    ISSN (online) 1089-8638
    ISSN 0022-2836
    DOI 10.1016/j.jmb.2023.168208
    Database NAL-Catalogue (AGRICOLA)

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    In stock of ZB MED Bonn / Germany

    Z 4' 63/108: Show issues

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  8. Article: Editorial: Intelligent Systems for Genome Functional Annotations.

    Ahmad, Shandar / Ballester, Pedro J / Fernandez, Michael

    Frontiers in genetics

    2020  Volume 11, Page(s) 915

    Language English
    Publishing date 2020-08-25
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2606823-0
    ISSN 1664-8021
    ISSN 1664-8021
    DOI 10.3389/fgene.2020.00915
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Predictive modeling of moonlighting DNA-binding proteins.

    Varghese, Dana Mary / Nussinov, Ruth / Ahmad, Shandar

    NAR genomics and bioinformatics

    2022  Volume 4, Issue 4, Page(s) lqac091

    Abstract: Moonlighting proteins are multifunctional, single-polypeptide chains capable of performing multiple autonomous functions. Most moonlighting proteins have been discovered through work unrelated to their multifunctionality. We believe that prediction of ... ...

    Abstract Moonlighting proteins are multifunctional, single-polypeptide chains capable of performing multiple autonomous functions. Most moonlighting proteins have been discovered through work unrelated to their multifunctionality. We believe that prediction of moonlighting proteins from first principles, that is, using sequence, predicted structure, evolutionary profiles, and global gene expression profiles, for only one functional class of proteins in a single organism at a time will significantly advance our understanding of multifunctional proteins. In this work, we investigated human moonlighting DNA-binding proteins (mDBPs) in terms of properties that distinguish them from other (non-moonlighting) proteins with the same DNA-binding protein (DBP) function. Following a careful and comprehensive analysis of discriminatory features, a machine learning model was developed to assess the predictability of mDBPs from other DBPs (oDBPs). We observed that mDBPs can be discriminated from oDBPs with high accuracy of 74% AUC of ROC using these first principles features. A number of novel predicted mDBPs were found to have literature support for their being moonlighting and others are proposed as candidates, for which the moonlighting function is currently unknown. We believe that this work will help in deciphering and annotating novel moonlighting DBPs and scale up other functions. The source codes and data sets used for this work are freely available at https://zenodo.org/record/7299265#.Y2pO3ctBxPY.
    Language English
    Publishing date 2022-12-02
    Publishing country England
    Document type Journal Article
    ISSN 2631-9268
    ISSN (online) 2631-9268
    DOI 10.1093/nargab/lqac091
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Inadequacy of Evolutionary Profiles Vis-a-vis Single Sequences in Predicting Transient DNA-Binding Sites in Proteins.

    Arya, Ajay / Mary Varghese, Dana / Kumar Verma, Ajay / Ahmad, Shandar

    Journal of molecular biology

    2022  Volume 434, Issue 13, Page(s) 167640

    Abstract: Sequence-based prediction of DNA-binding residues in a protein is a widely studied problem for which machine learning methods with continuously improving predictive power have been developed. Concatenated rows within a sliding window of a Position ... ...

    Abstract Sequence-based prediction of DNA-binding residues in a protein is a widely studied problem for which machine learning methods with continuously improving predictive power have been developed. Concatenated rows within a sliding window of a Position Specific Substitution Matrix (PSSM) of the protein are currently used as the primary feature set in almost all the methods of predicting DNA-binding residues. Here we report that these evolutionary profiles are powerful, only for identifying conserved binding sites and fall short for the residue positions which undergo binding to non-binding transitions in closely related proteins. We created a database of highly similar protein pairs with known protein-DNA complexes and investigated differential predictability of conserved and transient binding residues within each pair. Retraining machine learning models uniformly, we compared the predictive powers of the models trained on PSSMs against similarly trained models on sparse-encoded single sequences. We found that the transient binding site predictions from evolutionary profiles are outperformed by single-sequence based models under controlled experiments by as much as 8 percentage points. Thus, we conclude that the PSSM-based models are inadequate to predict high-specificity DNA-binding residues. These findings are of critical significance for the design of mutant- and species-specific DNA ligands and for homology based modeling of protein-DNA complexes.
    MeSH term(s) Binding Sites ; Computational Biology/methods ; DNA/metabolism ; Databases, Protein ; Ligands ; Protein Binding ; Proteins/chemistry
    Chemical Substances Ligands ; Proteins ; DNA (9007-49-2)
    Language English
    Publishing date 2022-05-18
    Publishing country Netherlands
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 80229-3
    ISSN 1089-8638 ; 0022-2836
    ISSN (online) 1089-8638
    ISSN 0022-2836
    DOI 10.1016/j.jmb.2022.167640
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 867: Show issues Location:
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    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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