Prof. Shoba Ranganathan

Prof. Shoba Ranganathan

Professor of Bioinformatics,
Department of Chemistry and Biomolecular Sciences

Contact details

F7B-4 WALLY’S WALK 121, Macquarie University
Phone: +61 (2) 9850 6262, Fax: +61 (2) 9850 8313
LinkedIn: Shoba Ranganathan 

ORCID: 0000-0002-8290-813X 

Shoba Ranganathan holds a Chair in Bioinformatics at Macquarie University since 2004. She has held research and academic positions in India, USA, Singapore, and Australia as well as a consultancy in industry. Shoba’s research addresses several key areas of bioinformatics to understand biological systems using computational approaches. Her group has achieved both experience and expertise in different aspects of computational biology, ranging from metabolites and small molecules to biochemical networks, pathway analysis, and computational systems biology. She has authored as well as edited several books as well as contributed several articles to Springer’s Encyclopedia of Systems Biology. She is currently the Editor-in-Chief of Elsevier’s Encyclopedia of Bioinformatics and Computational Biology as well as the Bioinformatics Section Editor for Elsevier’s Reference Module in Life Sciences.

About me

  • Professor Shoba Ranganathan has studied and worked in the field of bioinformatics since 1983, when the field was known as theoretical biochemistry and subsequently as biocomputing. She collaborated with pioneers in this discipline at the Institut de Biologie Physico-Chimique in Paris, funded by the Rothschild Foundation and associated to CNRS and has continued to be a leading player in bioinformatics throughout her career.
  • Shoba Ranganathan was the first Chair in Bioinformatics in Australia at Macquarie University and is Adjunct Professor at the National University of Singapore (since 2004). Her research interests include genome annotation, transcriptome analysis, structural bioinformatics, immunoinformatics, genome-phenome analysis, biological networks, biodiversity informatics and cheminformatics. Shoba’s achievements include the development of graph-theoretical methods for alternative splicing analysis, a rapid and accurate docking protocol for vaccine design, pipelines for assembly and annotation of transcriptomic data, especially from helminth parasites and network approaches for large scale data mining.
  • Shoba served as the first Australian Director of the International Society for Computational Biology (2003-5) and is currently the President of the Asia-Pacific Bioinformatics Network. Shoba serves on the editorial boards of several bioinformatics journals including PLoS One and BMC Bioinformatics, and contributes to the organisation and scientific program of several international bioinformatics conferences. She is a steering committee member of the International Immunomics Society and of Bioinformatics Australia. She is also a Bioinformatics and Biostatistics expert advisory panel member to the National Health & Medical Research Council, Australia since 2012.
  • Shoba hosted InCoB2014 in Sydney, Australia.


Curriculum vitae with publications


Research interests

Shoba’s research interests are in the area of computational biology and bioinformatics. Specific examples of her recent research are outlined below.

Alternative splicing:

  • Alternative pre-mRNA splicing is an important mechanism for controlling gene expression in higher eukaryotes. A single gene produces several functionally diverse proteins by alternative usage of exons or introns within pre-mRNA transcripts. These gene products can be specific to tissue, developmental stage, and disease state. We have pioneered the use of graph theory for genome-wide analysis of alternative splicing in the fruitfly, chicken compared to mouse and human and more recently, the cow, contributing to the annotation of the bovine genome as well as where the cow can be used as a model for human diseases.


  • Major histocompatibility complexes (MHC) play a vital role for antigen presentation and recognition by binding immunogenic peptide epitopes (p) and forming peptide-MHC (pMHC) complexes, for recognition by T cell receptors (TR), culminating in T cell activation. For efficient vaccine design and to minimize experimental T cell binding assays, advanced computational strategies for predicting strong MHC-binding epitopes with high propensity to activate T cells are required. By developing a fast accurate method for pMHC binding and analysing the physicochemical basis of TR binding to pMHC, we can accurately predicted T cell epitopes amongst high-binders for disease-implicated human MHC alleles.

Protein interaction networks:

  • Biological processes are governed by generic rules embedded in the complex connectivity or networks. Systematic studies over the past few years have unveiled how these rules maintain cellular complexity by coordinating a large number of biological processes and their molecular components. Integrating data from protein-protein and metabolite-linked protein interaction networks, we have compared, contrasted and analysed the statistical properties across different subcellular compartments. Our results indicate that the metabolic network adds value to the information in the protein interaction network for the localisation process of proteins in human subcellular compartments.


  • Parasitic nematodes infect humans, other animals and plants, and impose a significant public health and economic burden worldwide due to the diseases that they cause. A better understanding of parasite genomes, host-parasite relationships and the molecular biology of parasites themselves will enable the rational development of diagnostic tests and/or safe anti-parasitic compounds, following the functional annotation of parasite genomic sequences. With only a few completely sequenced nematode genomes, expressed sequence tag (EST) data-sets provide a low-cost alternative (“poor man’s genome”) to whole genome sequences and a glimpse of the transcriptome of an organism. EST data require a number of computational methods for their pre-processing, clustering, assembly and annotation to yield biologically relevant information. We have developed semi-automated bioinformatic pipelines, ESTExplorer and EST2Secretome to identify molecules involved in key biological processes or pathways that might serve as targets for new drugs or vaccines.

Biodiversity and Chem Informatics:

  • Biodiversity informatics is emerging as a discipline focusing on the collection, digitisation, collation, dissemination and analysis of species-level data. We have applied biodiversity informatics tools and resources to conserve and protect customary Aboriginal medicinal plants (CMP) and their associated indigenous knowledge. In collaboration with Aboriginal communities, a web-based multidisciplinary customary medicinal knowledgebase (CMKb) was developed as a unique Australian resource. GIS and ecological niche modeling techniques were used to identify CMP species-rich areas and evaluate the cultural worth of the habitats. Further, to understand the likely impacts of climate change on the areas of highest cultural worth, predictive models were developed for current and future climate scenarios, based on spatial distributions of select CMP species.
  • Bioactive compounds from natural sources are lead compounds for many therapeutic agents. Starting from the bioactive compounds in CMKb, we have carried out cheminformatics analysis of large public datasets as well as used machine learning methdos to predict novel lead molecules.


(from 2013; for full list organized as themes, see CV)


  • Hardianto A, Yusuf M, Liu F, Ranganathan S (2017) Exploration of charge states of balanol analogues acting as ATP-competitive inhibitors in kinases. BMC Bioinformatics. 18(Suppl 16):57.
  • Mohamedali A, Ahn SB, Sreenivasan VKA, Ranganathan S, Baker MS (2017) Human Prestin: A Candidate PE1 Protein Lacking Stringent Mass Spectrometric Evidence? J Proteome Res. 16, 4531-4535.
  • Jiao X, Ranganathan S (2017) Prediction of interface residue based on the features of residue interaction network. J Theor Biol. 432:49-54.
  • Baker MS, Ahn SB, Mohamedali A, Islam MT, Cantor D, Verhaert PD, Fanayan S, Sharma S, Nice EC, Connor M, Ranganathan S (2017) Accelerating the search for the missing proteins in the human proteome. Nat Commun. 8, 14271.
  • Patel AR, Hardianto A, Ranganathan S, Liu F (2017) Divergent response of homologous ATP sites to stereospecific ligand fluorination for selectivity enhancement. Org Biomol Chem. 15, 1570-1574.
  • Ranganathan S. (2017) Bioinformatics. In: Roitberg BD, Cotter PD, Dixon B, Giordano A, O’Neill SD, Pentimalli F, Ranganathan S, Sharfstein ST, Vitale I, Wilson K, Yelon D, Zarafoza O, Zhou HX (Eds) Reference Module in Life Sciences, Elsevier, ISBN: 978-0-12-809633-8
  • Islam MT, Mohamedali A, Ahn SB, Nawar I, Baker MS, Ranganathan S (2017) A systematic bioinformatics approach to identify high quality MS data and functionally annotate proteins and proteomes. In: Methods in Molecular Biology, 1549, 163-176. doi: 1007/978-1-4939-6740-7_13.
  • Islam MT, Mohamedali A, Fernandes CF, Baker MS, Ranganathan S (2017) De novo peptide sequencing: deep mining of high-resolution mass spectrometry data. In: Methods in Molecular Biology, 1549, 119-134. doi: 10.1007/978-1-4939-6740-7_10.



  • Schönbach C, Verma C, Bond PJ, Ranganathan S (2016) Bioinformatics and systems biology research update from the 15th International Conference on Bioinformatics (InCoB2016). BMC Bioinformatics. 17 Suppl 19, 524.
  • Schönbach C, Verma C, Wee LJ, Bond PJ, Ranganathan S (2016) 2016 update on APBioNet’s annual international conference on bioinformatics (InCoB). BMC Genomics. 17 Suppl 13,1036.
  • Liu F, Koval M, Ranganathan S, Fanayan S, Hancock WS, Lundberg EK, Beavis RC, Lane L, Duek P, McQuade L, Kelleher NL, Baker MS (2016) Systems Proteomics View of the Endogenous Human Claudin Protein Family. J Proteome Res. 15, 339-59.
  • Roitberg BD, Cotter PD, Dixon B, Giordano A, O’Neill SD, Pentimalli F, Ranganathan S, Sharfstein ST, Vitale I, Wilson K, Yelon D, Zarafoza O, Zhou HX (Eds) (2016) Reference Module in Life Sciences, Elsevier, ISBN: 978-0-12-809633-8


  • Schönbach C, Horton P, Yiu SM, Tan TW, Ranganathan S (2015) GIW and InCoB, two premier bioinformatics conferences in Asia with a combined 40 years of history. BMC Genomics. 16 Suppl 12, I1.
  • Schönbach C, Horton P, Yiu SM, Tan TW, Ranganathan S (2015) GIW and InCoB are advancing bioinformatics in the Asia-Pacific. BMC Bioinformatics. 16 Suppl 18, I1.
  • Sowmya G, Ranganathan S (2015) Discrete structural features among interface residue-level classes. BMC Bioinformatics. 16 Suppl 18, S8.
  • Horton P, Schönbach C, Ranganathan S, Yiu SM (2015) Introduction to selected papers from GIW/InCoB 2015. J Bioinform Comput Biol. 13,1502003.
  • Sowmya G, Breen EJ, Ranganathan S (2015) Linking structural features of protein complexes and biological function. Protein Sci. 24, 1486-94.
  • Horvatovich P, Lundberg EK, Chen YJ, Sung TY, He F, Nice EC, Goode RJ, Yu S, Ranganathan S, Baker MS, Domont GB, Velasquez E, Li D, Liu S, Wang Q, He QY, Menon R, Guan Y, Corrales FJ, Segura V, Casal JI, Pascual-Montano A, Albar JP, Fuentes M, Gonzalez-Gonzalez M, Diez P, Ibarrola N, Degano RM, Mohammed Y, Borchers CH, Urbani A, Soggiu A, Yamamoto T, Salekdeh GH, Archakov A, Ponomarenko E, Lisitsa A, Lichti CF, Mostovenko E, Kroes RA, Rezeli M, Végvári Á, Fehniger TE, Bischoff R, Vizcaíno JA, Deutsch EW, Lane L, Nilsson CL, Marko-Varga G, Omenn GS, Jeong SK, Lim JS, Paik YK, Hancock WS (2015) Quest for Missing Proteins: Update 2015 on Chromosome-Centric Human Proteome Project. J Proteome Res. 14, 3415-31.
  • Sadia M, Ahn SB, Cheruku HR, Cantor D, Rennel E, Fredriksson S, Edfeldt G, Breen EJ, Khan A, Mohamedali A, Muktadir MG, Ranganathan S, Tan SH, Nice E, Baker MS(2015) A novel multiplexed immunoassay identifies CEA, IL-8 and prolactin as prospective markers for Dukes’ stages A-D colorectal cancers. Clinical Proteomics, 12, 10.
  • Atwood TK, Bongcam-Rudloff E, Brazas ME, Corpas M, Gaudet P, Lewitter F, Mulder N, Palagi PM, Schneider MV, van Gelder CW, GOBLET Consortium (including Ranganathan S) (2015) GOBLET: The Global Organisation for Bioinformatics Learning, Education and Training. PLoS Comput Biol. 11, e1004143.
  • Alexander I, Hallwirth C, Garg G, Peters T, Kramer B, Malani N, Hyman J, Ruan X, Ginn S, Hetherington N, Veeravalli L, Shahab A, Ranganathan S, Wei CL, Liddle C, Thrasher A, Bushman F, Buckley M (2015) Coherence analysis discriminates between retroviral integration patterns in CD34+ cells transduced under differing clinical trial conditions. Molecular Therapy – Methods and Clinical Development, 2, 15015.
  • Khanna V, Ranganathan S (2015) Chemogenomics approach to computer-aided drug discovery. In: Sakharkar K, Sakharkar MK, Chandra R (Eds.) Post-Genomic Approaches in Drug and Vaccine Development, River Publishers, ISBN: 9788793102842, 91-111.


  • Tang YT, Gao X, Rosa BA, Abubucker S, Hallsworth-Pepin K, Martin J, Tyagi R, Heizer E, Zhang X, Bhonagiri-Palsikar V, Minx P, Warren WC, Zhan B, Hotez PJ, Sternberg PW, Dougall A, Gaze ST, Bethony J, Mulvenna J, Ranganathan S, Rabelo EM, Wilson RW, Felgner PL, Hawdon JM, Gasser RB, Loukas A, Mitreva M (2014) Genome of the human hookworm Necator americanus. Nature Genetics, 46, 261–269.
  • Ranganathan S, Tan T, Schönbach C. (2014) InCoB2014: Systems Biology update from the Asia-Pacific. BMC Syst Biol. 8 Suppl 4, I1.
  • Schönbach C, Tan T, Ranganathan S. (2014) InCoB2014: mining biological data from genomics for transforming industry and health. BMC Genomics. 15 Suppl 9, I1.
  • Ranganathan S, Tan T, Schönbach C. (2014) InCoB2014: bioinformatics to tackle the data to knowledge challenge. BMC Bioinformatics. 15 Suppl 16, I1.
  • Ahn SB, Mohamedali A, Anand S, Cheruku HR, Birch D, Sowmya G, Cantor D, Ranganathan S, Inglis DW, Frank R, Agrez M, Nice EC, Baker MS. Characterization of the interaction between heterodimeric αvβ6 integrin and urokinase plasminogen activator receptor (uPAR) using functional proteomics. J Proteome Res. 13, 5956-5964.
  • Sowmya G, Khan JM, Anand S, Ahn SB, Baker MS, Ranganathan S (2014) A site for direct integrin αvβ6•uPAR interaction from structural modelling and docking. J Struct Biol, 185, 327-335.
  • Krajaejun T, Lerksuthirat T, Garg G, Lowhnoo T, Yingyong W, Khositnithikul R, Tangphatsornruang S, Suriyaphol P, Ranganathan S, Sullivan TD (2014) Transcriptome Analysis Reveals Pathogenicity and Evolutionary History of the Pathogenic Oomycete Pythium insidiosum. Fungal Biol, 118, 640-653.
  • Islam MT, Garg G, Hancock WS, Risk BA, Baker MS, Ranganathan S (2014) Protannotator: A Semiautomated Pipeline for Chromosome-Wise Functional Annotation of the “Missing” Human Proteome. J Proteome Res. 13, 76-83.
  • Ranganathan S (2014) Advanced in silico analysis of expressed sequence tag (EST) data for parasitic nematodes of major socio-economic importance. In: Noor, NM (ed.) Bioinformatics in Systems Biology & Cryopreservation in Agrobiodiversity. Penerbit University Kebangsan Malaysia, Selangor, Malaysia, ISBN: 978-967-412-247-8, pp. 35-57.
  • Sowmya G, Ranganathan S (2014) Protein-protein interactions and prediction: a comprehensive overview. Peptide & Protein Letters, 21, 779-789. (invited)


  • Islam MT, Mohamedali A, Garg G, Khan JM, Gorse AD, Parsons J, Marshall P, Ranganathan S*, Baker MS* (2013) Unlocking the Puzzling Biology of the Black Périgord Truffle Tuber melanosporum. J Proteome Res. 12, 5349-56. (joint corresponding authors)
  • Khan AM, Tan TW, Schönbach C, Ranganathan S (2013) APBioNet – transforming bioinformatics in the Asia-Pacific Region. PLoS Comput Biol, invited editorial, 9, e1003317.
  • Schönbach C, Shen B, Tan TW, Ranganathan S (2013) InCoB2013 introduces Systems Biology as a major conference theme. BMC Systems Biology, 7(Suppl 3), S1.
  • Tan TW, Xie C, De Silva M, Lim KS, Patro CPK, Lim SJ, Govindarajan KR, Tong JC, Choo KH, Ranganathan S, Khan AM (2013) Simple re-instantiation of small databases using cloud computing. BMC Genomics, 14(Suppl 5), S13
  • Garg G, Bernal B, Trelis M, Forment J, Ortiz J, Valero ML, Pedrola L, Martinez-Blanch J, Esteban JG, Ranganathan S, Toledo R, Marcilla A (2013) The transcriptome of Echinostoma caproni adults: further characterization of the secretome and identification of new potential drug targets. J Proteomics, 89:202-14.
  • Kumar G, Breen EJ, Ranganathan S (2013) Identification of ovarian cancer associated genes using an integrated approach in a Boolean framework. BMC Systems Biology, 7:12.
  • Ranganathan S, Khan JM, Garg G, Baker MS (2013) Functional Annotation of the Human Chromosome 7 “Missing” Proteins: A Bioinformatics Approach. J Proteome Res, 12, 2504-25
  • Ranganathan S (2013) Adaptive Immune System. In: Dubitzky W, Wolkenhauer O, Cho K, Yokota H (Ed.) Encyclopedia of Systems Biology: SpringerReference ( Springer-Verlag Berlin Heidelberg. URL:
  • Ranganathan S (2013) T cell Signaling. In: Dubitzky W, Wolkenhauer O, Cho K, Yokota H (Ed.) Encyclopedia of Systems Biology: SpringerReference ( Springer-Verlag Berlin Heidelberg. URL:
  • Ranganathan S (2013) T Cell Activation. In: Dubitzky W, Wolkenhauer O, Cho K, Yokota H (Ed.) Encyclopedia of Systems Biology: SpringerReference ( Springer-Verlag Berlin Heidelberg.  URL:\\
  • Ranganathan S (2013) Structural Immunoinformatics. In: Dubitzky W, Wolkenhauer O, Cho K, Yokota H (Ed.) Encyclopedia of Systems Biology: SpringerReference ( Springer-Verlag Berlin Heidelberg. URL:
  • Ranganathan S (2013) Reverse Vaccinology. In: Dubitzky W, Wolkenhauer O, Cho K, Yokota H (Ed.) Encyclopedia of Systems Biology: SpringerReference ( Springer-Verlag Berlin Heidelberg. URL:
  • Ranganathan S (2013) T Cell Epitopes. In: Dubitzky W, Wolkenhauer O, Cho K, Yokota H (Ed.) Encyclopedia of Systems Biology: SpringerReference ( Springer-Verlag Berlin Heidelberg.  URL:
  • Ranganathan S (2013) TR Germline Bias. In: Dubitzky W., Wolkenhauer O., Cho K., Yokota H. (Ed.) Encyclopedia of Systems Biology: SpringerReference ( Springer-Verlag Berlin Heidelberg, 2013. URL:
  • Ranganathan S (2013) pMHC epitope. In: Dubitzky W, Wolkenhauer O, Cho K, Yokota H (Ed.) Encyclopedia of Systems Biology: SpringerReference ( Springer-Verlag Berlin Heidelberg. URL:
  • Khan J, Ranganathan S (2013) TR recognition of MHC-peptide complexes. In: Dubitzky W, Wolkenhauer O, Cho K, Yokota H (Ed.) Encyclopedia of Systems Biology: SpringerReference ( Springer-Verlag Berlin Heidelberg. DOI: 10.1007/SpringerReference_306267
  • Garg G, Ranganathan S (2013) High-throughput functional annotation and data mining of fungal genomes to identify therapeutic targets. In: Eds. Gupta VK, Tuohy M, Ayyachamy M, Turner KM, O’Donovan A. Laboratory protocols in fungal biology: current methods in fungal biology. Springer, New York, USA. ISBN 978-1-4614-2355-3, Invited book chapter, pp.559-564.
  • Kumar G, Ranganathan S (2013) Biological data integration using network models. In: Elloumi M, Zomaya AY (Eds). Biological Knowledge Discovery Handbook: Prepossessing, Mining and Postprocessing of Biological Data, Wiley Series in Bioinformatics. John Wiley & Sons, New Jersey. ISBN: 978-1-1181-3273-9, pp.155-173, invited chapter.
  • Tong JC, Ranganathan S (2013) Computer-aided vaccine design, Woodhead Publishing Series in Biomedicine No. 23, Woodhead, Cambridge, UK, pp 1-164.