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  1. AU="Varadwaj, Pritish K"
  2. AU="Bachiller-Hernández, Jaime"
  3. AU="MarinBenito, C"
  4. AU="Proto, Alice"
  5. AU="Stojanovic, Jelena"
  6. AU="Vargas Zhang, Adrian"
  7. AU="Braine, Rebecca"
  8. AU="Santos, Christine Nicole S"
  9. AU="Severi, Kristen E"
  10. AU="Robotti, Marzia"
  11. AU="Kaspar, Charles W"
  12. AU="Wallach, E E"
  13. AU="Temnikov, P"
  14. AU="Gomez-Verjan, Juan Carlos"
  15. AU="Mayle, Francis E."
  16. AU="Rhoades, Elizabeth"
  17. AU="Riaz, Huma"
  18. AU="Eliseu, Gabriel"
  19. AU="Hill, Lori R"
  20. AU="Boppana, Suresh B"

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  1. Artikel: Understanding the Mechanism of Cell Death in Gemcitabine Resistant Pancreatic Ductal Adenocarcinoma: A Systems Biology Approach.

    Aier, Imlimaong / Varadwaj, Pritish K

    Current genomics

    2020  Band 20, Heft 7, Seite(n) 483–490

    Abstract: Background: Gemcitabine is the standard chemotherapeutic drug administered in advanced Pancreatic Ductal Adenocarcinoma (PDAC). However, due to drug resistance in PDAC patients, this treatment has become less effective. Over the years, clinical trials ... ...

    Abstract Background: Gemcitabine is the standard chemotherapeutic drug administered in advanced Pancreatic Ductal Adenocarcinoma (PDAC). However, due to drug resistance in PDAC patients, this treatment has become less effective. Over the years, clinical trials for the quest of finding novel compounds that can be used in combination with gemcitabine have met very little success.
    Objective: To predict the driving factors behind pancreatic ductal adenocarcinoma, and to understand the effect of these components in the progression of the disease and their contribution to cell growth and proliferation.
    Methods: With the help of systems biology approaches and using gene expression data, which is generally found in abundance, dysregulated elements in key signalling pathways were predicted. Prominent dysregulated elements were integrated into a model to simulate and study the effect of gemcitabine-induced hypoxia.
    Results: In this study, several transcription factors in the form of key drivers of cancer-related genes were predicted with the help of CARNIVAL, and the effect of gemcitabine-induced hypoxia on the apoptosis pathway was shown to have an effect on the downstream elements of two primary pathway models; EGF/VEGF and TNF signalling pathway.
    Conclusion: It was observed that EGF/VEGF signalling pathway played a major role in inducing drug resistance through cell growth, proliferation, and avoiding cell death. Targeting the major upstream components of this pathway could potentially lead to successful treatment.
    Sprache Englisch
    Erscheinungsdatum 2020-01-02
    Erscheinungsland United Arab Emirates
    Dokumenttyp Journal Article
    ZDB-ID 2033677-9
    ISSN 1875-5488 ; 1389-2029
    ISSN (online) 1875-5488
    ISSN 1389-2029
    DOI 10.2174/1389202920666191025102726
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel ; Online: DeepOlf: Deep Neural Network Based Architecture for Predicting Odorants and Their Interacting Olfactory Receptors.

    Sharma, Anju / Kumar, Rajnish / Semwal, Rahul / Aier, Imlimaong / Tyagi, Pankaj / Varadwaj, Pritish K

    IEEE/ACM transactions on computational biology and bioinformatics

    2022  Band 19, Heft 1, Seite(n) 418–428

    Abstract: Olfaction transduction mechanism is triggered by the binding of odorants to the specific olfactory receptors (OR's) present in the nasal cavity. Different odorants stimulate different OR's due to the difference in shape, physical and chemical properties. ...

    Abstract Olfaction transduction mechanism is triggered by the binding of odorants to the specific olfactory receptors (OR's) present in the nasal cavity. Different odorants stimulate different OR's due to the difference in shape, physical and chemical properties. In this paper, a deep neural network architecture DeepOlf, based on molecular features and fingerprints of odorants and ORs, to predict whether a chemical compound is a potential odorant or not along with its interacting OR is proposed. Odorant identification and Odorant-OR interaction were modeled as a binary classification through multiple classifiers. The evaluation of these classifier's performance showed that the deep-neural network framework not only fits data with better accuracy in comparison to other classical methods (SVM, RF, k-NN) but also able to predict odorant-OR interactions more accurately. To our knowledge, this study is the first realization of deep learning ideas for the problem of odorant and interacting OR prediction. The accuracy of DeepOlf was found to be 94.83 and 99.92 percent for the prediction of odorants and Odorant- OR interactions respectively. Comparison of DeepOlf prediction with the existing SVM based prediction server, ODORactor, showed that better performance can be achieved with the proposed deep learning approach. The DeepOlf tool can be accessed at https://bioserver.iiita.ac.in/deepolf/.
    Mesh-Begriff(e) Neural Networks, Computer ; Odorants ; Receptors, Odorant/genetics
    Chemische Substanzen Receptors, Odorant
    Sprache Englisch
    Erscheinungsdatum 2022-02-03
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ISSN 1557-9964
    ISSN (online) 1557-9964
    DOI 10.1109/TCBB.2020.3002154
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel: Deciphering the Novel Target Genes Involved in the Epigenetics of Hepatocellular Carcinoma Using Graph Theory Approach.

    Roy, Nimisha / Raj, Utkarsh / Rai, Sneha / Varadwaj, Pritish K

    Current genomics

    2020  Band 20, Heft 8, Seite(n) 545–555

    Abstract: Background: Even after decades of research, cancer, by and large, remains a challenge and is one of the major causes of death worldwide. For a very long time, it was believed that cancer is simply an outcome of changes at the genetic level but today, it ...

    Abstract Background: Even after decades of research, cancer, by and large, remains a challenge and is one of the major causes of death worldwide. For a very long time, it was believed that cancer is simply an outcome of changes at the genetic level but today, it has become a well-established fact that both genetics and epigenetics work together resulting in the transformation of normal cells to cancerous cells.
    Objective: In the present scenario, researchers are focusing on targeting epigenetic machinery. The main advantage of targeting epigenetic mechanisms is their reversibility. Thus, cells can be reprogrammed to their normal state. Graph theory is a powerful gift of mathematics which allows us to understand complex networks.
    Methodology: In this study, graph theory was utilized for quantitative analysis of the epigenetic network of hepato-cellular carcinoma (HCC) and subsequently finding out the important vertices in the network thus obtained. Secondly, this network was utilized to locate novel targets for hepato-cellular carcinoma epigenetic therapy.
    Results: The vertices represent the genes involved in the epigenetic mechanism of HCC. Topological parameters like clustering coefficient, eccentricity, degree,
    Conclusion: The top ten novel epigenetic target genes involved in HCC reported in this study are cdk6, cdk4, cdkn2a, smad7, smad3, ccnd1, e2f1, sf3b1, ctnnb1, and tgfb1.
    Sprache Englisch
    Erscheinungsdatum 2020-06-11
    Erscheinungsland United Arab Emirates
    Dokumenttyp Journal Article
    ZDB-ID 2033677-9
    ISSN 1875-5488 ; 1389-2029
    ISSN (online) 1875-5488
    ISSN 1389-2029
    DOI 10.2174/1389202921666191227100441
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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    Verfügbar in ZB MED Köln/Königswinter

    Zs.A 5571: Hefte anzeigen Standort:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  4. Artikel: Transcriptomic Analysis of Soil Grown

    Gupta, Saurabh / Yadav, Brijesh S / Raj, Utkarsh / Freilich, Shiri / Varadwaj, Pritish K

    Frontiers in plant science

    2017  Band 8, Seite(n) 1025

    Abstract: Deficiency of necessary macronutrients, i.e., Potassium (K), Magnesium (Mg), Nitrogen (N), Phosphorus (P), and Sulfate (S) in the soil leads to a reduction in plant growth and yield, which is a result of changes in expression level of various genes. This ...

    Abstract Deficiency of necessary macronutrients, i.e., Potassium (K), Magnesium (Mg), Nitrogen (N), Phosphorus (P), and Sulfate (S) in the soil leads to a reduction in plant growth and yield, which is a result of changes in expression level of various genes. This study was performed to identify the differentially expressed genes and its associated metabolic pathways occurred in soil grown wheat root samples excavated from the control and treated fields. To identify the difference in gene expression levels due to deficiency of the said nutrients, a transcriptomic, meta-analysis was performed on array expression profile data. A set of 435 statistically significant probes encoding 398 Nutrient Deficiency Response Genes (NRGs) responding at-least one nutrients deficiency (ND) were identified. Out of them 55 NRGs were found to response to minimum two ND. Singular Enrichment Analysis (SEA) predicts ontological based classifications and functional analysis of NRGs in different cellular/molecular pathways involved in root development and growth. Functional annotation and reaction mechanism of differentially expressed genes, proteins/enzymes in the different metabolic pathway through MapMan analysis were explored. Further the meta-analysis was performed to revels the active involvement each NRGs in distinct tissues and their comparative potential expression analysis in different stress conditions. The study results in exploring the role of major acting candidate genes such as Non-specific serine/threonine protein kinase, Xyloglucan endotransglucosylase/hydrolase, Peroxides, Glycerophosphoryl diester phosphodiesterase, S-adenosylmethionine decarboxylase proenzyme, Dehydrin family proteins, Transcription factors, Membrane Proteins, Metal binding proteins, Photosystem proteins, Transporter and Transferase associated in different metabolic pathways. Finally, the differences of transcriptional responses in the soil-grown root of
    Sprache Englisch
    Erscheinungsdatum 2017-06-22
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ZDB-ID 2711035-7
    ISSN 1664-462X
    ISSN 1664-462X
    DOI 10.3389/fpls.2017.01025
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  5. Artikel ; Online: Identification of Dual Natural Inhibitors for Chronic Myeloid Leukemia by Virtual Screening, Molecular Dynamics Simulation and ADMET Analysis.

    Kumar, Himansu / Raj, Utkarsh / Srivastava, Swati / Gupta, Saurabh / Varadwaj, Pritish K

    Interdisciplinary sciences, computational life sciences

    2016  Band 8, Heft 3, Seite(n) 241–252

    Abstract: Chronic myeloid leukemia (CML) is a disease of bone marrow stem cells caused by excessive growth and accumulation of granulocytes in the blood. Aberrant expression of the BCR-ABL proteins in bone marrow stem cells have found out in 95 % cases of CML. ... ...

    Abstract Chronic myeloid leukemia (CML) is a disease of bone marrow stem cells caused by excessive growth and accumulation of granulocytes in the blood. Aberrant expression of the BCR-ABL proteins in bone marrow stem cells have found out in 95 % cases of CML. Tyrosine Kinase domains (SH2 and SH3) of BCR-ABL proteins are the potent targets to inhibit the process. Initially, imatinib is preferred as an efficient inhibitor to control functional activity of disease. Recently, it has been reported that the advanced stage of CML developed resistance against imatinib. In continuation, dasatinib is the first drug to combat against this disease by targeting multiple receptors and proven better as compared to imatinib. Here, an attempt has been made to identify similar analogs of dasatinib. Virtual screening was performed against various natural compound databases to get some potent natural compounds which are able to inhibit more than one receptor. Binding affinity of screened natural compounds was compared with some of the well-known inhibitors like imatinib, dasatinib, nilotinib etc., by analyzing their docking score and binding efficiency with the receptor. Stability of the best ligand-receptor complex was checked by performing 10 ns molecular dynamics simulation. ADMET properties of the obtained screened compounds were analyzed to check drug like property. Based on the aforementioned analysis, it has been suggested that these screened potent compounds are capable to inhibit multiple receptor proteins like ABL and SRC and consequently combat against the deadly disease CML.
    Mesh-Begriff(e) Animals ; Antineoplastic Agents/chemistry ; Antineoplastic Agents/therapeutic use ; Computational Biology/methods ; Dasatinib/chemistry ; Dasatinib/therapeutic use ; Humans ; Imatinib Mesylate/chemistry ; Imatinib Mesylate/therapeutic use ; Leukemia, Myeloid/drug therapy ; Molecular Dynamics Simulation
    Chemische Substanzen Antineoplastic Agents ; Imatinib Mesylate (8A1O1M485B) ; Dasatinib (RBZ1571X5H)
    Sprache Englisch
    Erscheinungsdatum 2016-09
    Erscheinungsland Germany
    Dokumenttyp Journal Article
    ZDB-ID 2493085-4
    ISSN 1867-1462 ; 1913-2751
    ISSN (online) 1867-1462
    ISSN 1913-2751
    DOI 10.1007/s12539-015-0118-7
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  6. Artikel: Comparative Analysis of AGPase Genes and Encoded Proteins in Eight Monocots and Three Dicots with Emphasis on Wheat.

    Batra, Ritu / Saripalli, Gautam / Mohan, Amita / Gupta, Saurabh / Gill, Kulvinder S / Varadwaj, Pritish K / Balyan, Harindra S / Gupta, Pushpendra K

    Frontiers in plant science

    2017  Band 8, Seite(n) 19

    Abstract: ADP-glucose pyrophosphorylase (AGPase) is a heterotetrameric enzyme with two large subunits (LS) and two small subunits (SS). It plays a critical role in starch biosynthesis. We are reporting here detailed structure, function and evolution of the genes ... ...

    Abstract ADP-glucose pyrophosphorylase (AGPase) is a heterotetrameric enzyme with two large subunits (LS) and two small subunits (SS). It plays a critical role in starch biosynthesis. We are reporting here detailed structure, function and evolution of the genes encoding the LS and the SS among monocots and dicots. "True" orthologs of maize
    Sprache Englisch
    Erscheinungsdatum 2017-01-24
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ZDB-ID 2711035-7
    ISSN 1664-462X
    ISSN 1664-462X
    DOI 10.3389/fpls.2017.00019
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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