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LABORATORY SETUP
  • One Bench top cold centrifuge.
  • One Thermocycler (Amersham Biosciences) [48 well]
  • Tissue Culture set up with one Laminar Air Flow Cabinet.
  • Autoclave.
  • Biochemistry laboratory (fully equipped).
  • Vertical and Submarine gel apparatus.
  • Publications
    Journal Publications :
    1. "Complex molecular mechanisms underlying MYMIV-resistance in Vigna mungo revealed by comparative transcriptome profiling" Anirban Kundu, Pankaj Kumar Singh, Avishek Dey, Sayak Ganguli, and Amita Pal, Scientific Reports 2019 (In Press).
    2. Mitu De, Manisha Bhattacharya, Animita C. Saha, Indrani Basu, Sayak Ganguli and Santi Ranjan Dey Influence of Oral Microbiome on Human Health: an Overview Int J Adv Life Sci Res. Volume 2(1) 16-21 2019; doi: 10.31632/ijalsr.2019v02i01.003.
    3. PK Singh, S Ganguli, A Pal - Functions of long non-coding RNAs in plants: a riddle to explore; The Nucleus, Pg 1 - 12; 2018.
    4. Susmita Roy, Sujata Roy, Vineet Vishal, Sonia Bansal , Sayak Ganguli and Pratiti Ghosh. Comparative Study of Plant Derived Natural Compounds and Established inhibitors of P-Glycoprotein of Mouse and Human Using Molecular Docking. International Journal of Pharmacy and Biological Sciences. Vol 8. Issue 3, 228-233.
    5. Upal Das Ghosh, Pankaj K Singh, Sayak Ganguli, Chinmay Saha, Ayan Chandra, Anindita Seal and Mahashweta Mitra Ghosh, Comparative profiling of the rhzospheric soil of Typha augustifolia L from heavy metal contaminated and free sites reveals the selective abundance of ϒ -Proteobacteria and β-Proteobacteria. Indian Journal of Experimental Biology, 2018, (In Press). IF: 1.475.
    6. Shruti Chakraborty, Sayak Ganguli, Aritra Chowdhury, Michael Ibba, Rajat Banerjee: Reversible inactivation of yeast mitochondrial phenylalanyl-tRNA synthetase under oxidative stress,Biochimica et Biophysica Acta (BBA) - General Subjects,1862(8),2018,Pages 1801-1809. IF: 4.81.
    7. Pankaj Kumar Singh, Sayak Ganguli and Amita Pal: Screening and Identification of putative long non codingRNAs from transcriptome data of a high yielding blackgram (Vigna mungo), Cv. T9, Data in Brief (Elsevier): 17,Pages 459–462 ; 2018; https://doi.org/10.1016/j.dib.2018.01.043 IF: 0.287.
    8. Mitu De, Sayak Ganguli and Santi Ranjan Dey: MICROBIOME, HUMAN HEALTH AND BIOMARKERS: A BRIEF REVIEWHarvest (Online), Microbiome, Health & Biomarkers Volume 3(2); 37 - 48 2018.
    9. S Rahaman, A R Bera, V Vishal, P K Singh, and S Ganguli: A PHYLOGENETIC INSIGHT INTO THE FERN RHIZOSPHERE OF Acrostichum aureum Linn IJPBS, 8 (2) 2018; 452-456.
    10. Pankaj Kumar Singh, Anju Patel, Sayak Ganguli, Amita Pal: Molecular modeling and simulation of three important components of Plant Pathogen Interaction cascade in Vigna mungo Bioinformation 13(10): 323-326 (2017) IF: 1.37.
    11. Subhadipa Sengupta, Sayak Ganguli, Pankaj K Singh (2017): Metagenome analysis of the rootendophytic microbial community of Indian rice (O. sativa L.). Genomics Data 02/2017; 12., DOI:10.1016/j.gdata.2017.02.010 IF: 0.287.
    12. Joardar S., Ghosh S., Gupta S., Ganguli S., 2017. In vitro and computational assessment of genotoxic potential of active constituents present in three medicinally important plant extracts.Int.J.Curr.Res.Biosci.Plantbiol. 4(7): 119-128. doi: https://doi.org/10.20546/ijcrbp.2017.407.015
    13. S Rahaman, AR Bera, V Vishal, PK Singh, P Basu, S Gupta, M Basu, S Ganguli ISOLATION AND COMPUTATIONAL CHARACTERIZATION OF GLUTATHIONE PEROXIDASE GENE FROM AZOLLA PINNATA2017 RJLBPCS 3(2) 122 - 128.
    14. Ankush Pal, Biplab Bandyopadhyay, Santi Ranjan Dey, Sayak Ganguli, Pankaj Kumar Singh and Mitu DeDocumentation and Diversity Analysis by DNA Fingerprinting of the indigenous Mango (Mangifera indica L.) Germplasm of West Bengal; Int. J. Exp. Res. Rev., Vol. 11: 21-34 (2017).
    15. Anju Patel, Soumitra Maiti, Santosh Kumar, Sayak Ganguli, Amita Pal(2016): An Integrated Approach to Comprehend MYMIV-Susceptibility of Blackgram Cv. T9 Possessing Allele of CYR1 , the Cognate R-Gene. American Journal of Plant Sciences 01/2016; 07(02):267-278., DOI:10.4236/ajps.2016.72026 IF: 1.33.
    16. Sayak Ganguli, Avishek Dey, Rahul Banik, Anirban Kundu, Amita Pal: Analyses of MYMIV-induced transcriptome in Vigna mungo as revealed by next generation sequencing. Genomics Data 01/2016; 7(C)., DOI:10.1016/j.gdata.2016.01.005 {Featured Article of Lab Resource Segment) IF: 0.287.
    17. Santi Ranjan Dey, Pankaj K Singh, Sayak Ganguli, Mitu De: Seri - Bioinformatics : To Enhance Silken Touch. Journal of Environment and Sociobiology Vol 13 (2) 2016.
    18. Protip Basu, Sayak Ganguli, Hirak Jyoti Chakraborty, Abhijit Datta: Intrinsically Unstructured regions in Argonaute sequences across various domains of life. The Indian Journal of Physiology and Allied Sciences 2016.
    19. Aditi Gangopadhyay, Sayak Ganguli, Abhijit Datta: Identification of HIV -1 protease inhibitors using Oleanolic acid as reference ligand. The Indian Journal of Physiology and Allied Sciences 2016.
    20. Vineet Vishal, Pankaj K Singh, Abhisek Ranjan Bera, Protip Basu, Sayak Ganguli, Abhijit Datta: piRNA diversity across model species and humans revealed through Kohonen Maps. The Indian Journal of Physiology and Allied Sciences 2016.
    21. Damayanti Chakravarty, Pankaj K. Singh, Sabdar Rahaman, Sayak Ganguli : Identification of Pseudoknot in the Intergenic Region between VP30 and VP24 Gene of Ebola Virus and Designing Aptamer against the Pseudoknot. DOI:10.20546/ijcrbp.2016.305.008 2016.
    22. Sabdar Rahaman, Pankaj Kumar Singh, Protip Basu, Sohini Gupta, Monojit Basu, Sayak Ganguli : Isolation and Computational Characterization of Glutathione Peroxidase Gene from an Aquatic Fern - Salvinia molesta. 02/2016; 51:58-62., DOI:10.18052/www.scipress.com/ILNS.51.58IF: 0.51.
    23. Book Chapters :
    24. Datta A., Ganguli S. (2018) THE INTERACTOMICS OF THE RNA-INDUCED SILENCING COMPLEX. In: Wadhwa G., Shanmughavel P., Singh A., Bellare J. (eds) Current trends in Bioinformatics: An Insight. Springer, Singapore; https://doi.org/10.1007/978-981-10-7483-7_11.
    25. Sanga Mitra, Sayak Ganguli and Jayprokas Chakraborty: “INTRODUCTION TO NON CODING RNAS AND CANCER” Chapter 1 in Cancer and Noncoding RNAs; Elsevier. 2017. pg: 1 - 26.
    26. Shakri Banerjee, Damayanti Chakravarty, Sayak Ganguli and Susanta Roychowdhury: “CANCER NON CODING RNA DISCOVERY THROUGH HIGH THROUGHPUT SEQUENCING” ; Chapter 25 in Cancer and Noncoding RNAs; Elsevier. 2017.Pg 463 - 478.
    27. Sanga Mitra, Agnik Halder, Sohini Gupta, Sayak Ganguli and Jayprokas Chakraborty: A COMPARATIVE EVALUATION OF EMERGING DATABASES ANDTOOLS FOR CANCER NONCODING RNAS; Chapter 27; Pg 497 - 508.
    28. Aditi Gangopadhyay, Hirak Jyoti Chakraborty, Sayak Ganguli and Abhijit Datta : “PROTEIN STRUCTURE PREDICTION” - in Applying Big Data Analytics in Bioinformatics and Medicine, edited by: Miltiades D. Lytras and P. Papadopoulou, IGI GLOBAL Publications, USA, 2017 Chapter 8.
    Accession Numbers :
    1. SIX ACCESSION NUMBERS FOR GLUTATHIONE PEROXIDASE GENE EF620778 – EF62083 available publicly at NCBI – GENBANK Collection since 2007.
    2. NGS BASED TRANSCRIPTOME LIBRARY ACCESSION :
      1. A. BIOPROJECT ID: PRJNA288413; BIOSAMPLE: SAMN03799418; SRA ACCESSION: SRX1058325; SRX1058327. Study Title: Transcriptome Library of Mock Inoculated Vigna mungo cultivar T9; 1 LS454 (454 GS FLX+) run: 32.7M spots, 9.9G bases, 4.6Gb downloads. Study Title: Transcriptome Data of Vigna mungo Cv. T9 infected with MYMIV; 1 LS454 (454 GS FLX+) run: 30.6M spots, 9.2G bases, 4.3Gb downloads.
      2. BIOPROJECT ID: PRJNA283940; BIOSAMPLE: SAMN03658143; SRA ACCESSION: SRX1032950; SRX1082731 Study Title: Transcriptome Library of Vigna mungo RIL VM84 infected with MYMIV; 1 LS454 (454 GS FLX) run: 56.1M spots, 11.3G bases, 6.8Gb downloads. Study Title: Transcriptome Library of mock inoculated Vigna mungo RIL VM84; 1 LS454 (454 GS FLX) run: 39.7M spots, 8G bases, 4.8Gb downloads.
    3. NGS BASED METAGENOME LIBRARY ACCESSION :
      1. Metagenome or environmental sample from FERN rhizosphere of Indian Sunderbans Identifiers: BioSample: SAMN06606462; Sample name: ISRAa16; SRA: SRS2062634.
      2. Metagenome or environmental sample from root metagenome Identifiers:BioSample: SAMN06209718; Sample name: OS04; SRA: SRS1948687.
      3. Metagenome or environmental sample from root metagenome Identifiers:BioSample: SAMN06209694; Sample name: OS01; SRA: SRS1946070.
     
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