About Me

Hi! I'm Bobby Ranjan, a bioinformatics specialist at the Genome Institute of Singapore. Born in Scotland, raised in India and working in Singapore, I'm an ambitious student-researcher in the field of computational biology.


Bachelor of Engineering (B.E.) in Computer Engineering with
Minors in Entrepreneurship & Life Sciences

2014 - 2018

Nanyang Technological University, Singapore

Selected Publications

Hae-Ock Lee, Yourae Hong, Dr. Hakki Etlioglu, Yong Beom Cho, ..., Bobby Ranjan, ..., Shyam Prabhakar, Sabine Tejpar, Woong-Yang Park
Nature Genetics

Immunotherapy for metastatic colorectal cancer is effective only for mismatch repair-deficient tumors with high microsatellite instability that demonstrate immune infiltration, suggesting that tumor cells can determine their immune microenvironment. To understand this cross-talk, we analyzed the transcriptome of 91,103 unsorted single cells from 23 Korean and 6 Belgian patients. Cancer cells displayed transcriptional features reminiscent of normal differentiation programs, and genetic alterations that apparently fostered immunosuppressive microenvironments directed by regulatory T cells, myofibroblasts and myeloid cells. Intercellular network reconstruction supported the association between cancer cell signatures and specific stromal or immune cell populations. Our collective view of the cellular landscape and intercellular interactions in colorectal cancer provide mechanistic information for the design of efficient immuno-oncology treatment strategies.

scConsensus: An approach combining semi-supervised and unsupervised clustering for cell type annotation in single-cell RNA-seq data

Bobby Ranjan, Florian Schmidt, Wenjie Sun, Jinyu Park, Mohammad Amin Honardoost, Joanna Tan, Nirmala Arul Rayan and Shyam Prabhakar
April 2020
bioRXiv (Single Cell Analyses Meeting, Cold Spring Harbor Laboratory)

Background: Clustering is a crucial step in the analysis of single-cell data. Clusters identified in an unsupervised manner are typically annotated to cell types based on differentially expressed genes. In contrast, supervised methods use a reference panel of labelled transcriptomes to guide both clustering and cell type identification. Supervised and unsupervised clustering approaches have their distinct advantages and limitations. Therefore, they can lead to different but often complementary clustering results. Hence, a consensus approach leveraging the merits of both clustering paradigms could result in a more accurate clustering and a more precise cell type annotation.
Results: We present scConsensus, an R framework for generating a consensus clustering by (i) integrating the results from both unsupervised and supervised approaches and (ii) refining the consensus clusters using differentially expressed (DE) genes. The value of our approach is demonstrated on several existing single-cell RNA sequencing datasets, including data from sorted PBMC sub-populations.
Conclusions: scConsensus combines the merits of unsupervised and supervised approaches to partition cells with better cluster separation and homogeneity, thereby increasing our confidence in detecting distinct cell types. scConsensus is freely available on GitHub.

Bobby Ranjan
Final Year Project, Nanyang Technological University

Mapping the complete set of protein and gene interactions in the human cell has been a goal of the biological community for nearly two decades, since the first human genome was sequenced. To this end, computational approaches have been studied in depth to allow functional annotation of protein interactions. In this project, we explored the potential of using four common module detection algorithms - stochastic block model, Louvain method, modified Louvain (incremental Louvain) method and link community - in order to detect functional modules of for protein interaction networks. We implemented these algorithms in a Cytoscape application for users to run on their respective networks. Using this application, we conducted a comparative study of the algorithms to understand their applicability in protein function annotation and determine how close topological modules of protein-interaction networks are to their functional modules.

Bobby Ranjan, Ket Hing Chong and Zheng Jie
BMC Systems Biology - Volume 12 (The Sixteenth Asia-Pacific Bioinformatics Conference)

Background: Alzheimer's disease (AD) is a progressive neurological disorder, recognized as the most common cause of dementia affecting people aged 65 and above. AD is characterized by an increase in amyloid metabolism, and by the misfolding and deposition of β-amyloid oligomers in and around neurons in the brain. These processes remodel the calcium signaling mechanism in neurons, leading to cell death via apoptosis. Despite accumulating knowledge about the biological processes underlying AD, mathematical models to date are restricted to depicting only a small portion of the pathology.
Results: Here, we integrated multiple mathematical models to analyze and understand the relationship among amyloid depositions, calcium signaling and mitochondrial permeability transition pore(PTP)-related cell apoptosis in AD. The model was used to simulate calcium dynamics in the absence and presence of AD. In the absence of AD, i.e. without β-amyloid deposition, mitochondrial and cytosolic calcium level remains in the low resting concentration. However, our in silico simulation of the presence of AD with the β-amyloid deposition, shows an increase in the entry of calcium ions into the cell and dysregulation of Ca2+ channel receptors on the Endoplasmic Reticulum. This composite model enabled us to make simulation that is not possible to measure experimentally.
Conclusions: Our mathematical model depicting the mechanisms affecting calcium signaling in neurons can help understand AD at the systems level and has potential for diagnostic and therapeutic applications.


Bioinformatics Specialist

August 2018 - Present
Prabhakar Lab, Genome Institute of Singapore
  • Developing algorithms for cell type identification in single-cell data

Software Design Engineer Intern

May - August 2017
  • Built customer-facing license consumption report for all BitTitan products
  • Conducted tech feasibility analysis to improve BitTitan’s reporting capacity
  • Built code analysis tool to clean up database references across codebase

Technology Analyst Intern

August - December 2016
Bank of America, Merrill Lynch (Singapore)
  • Worked on the payments processing and payments testing development teams
  • Redesigned database logging using a queueing mechanism with the help of Apache ActiveMQ and Java Spring Framework
  • Also built an application to help onboard new testers onto the testing platform, using Java, AngularJS and SQL

Summer Intern

May - July 2016
Asia Risk Transfer Solutions (ARTS), Singapore

Asia Risk Transfer Solutions - a software and technological solutions startup that aims to help the insurance industry and governments create and manage risk transfer products, known as Insurance for the Masses, for developing communities in Asia.

  • Worked in a small team of 6 on Android application development for the company
  • Developed 2 MVP Android applications for different user groups
  • Enhanced server-side API of the enterprise web application
  • Tech stack included Java, Android and Django


ContextNewsBot - Context News Bot is a Chrome extension that allows you to step out of your filter bubble by providing a diverse set of news articles and objective Wikipedia entries for any tweet on your Twitter timeline.
CommandPlus - A Chrome extension that provides hand gesture-based control of one's browser.
CodeBot - An interactive chatbot that helps beginners learn how to code with witty replies, GIFs and human-readable errors.
When We Meet Again - An Android application that uses the relative distance between users, determined using the phone's Bluetooth, to trigger a reminder/push notification.
WhyBills - A system designed to eliminate printed bills at any point of sale by allowing retailers to encode their bill, generate a QR Code on our POS System and display this QR Code to the customer as a receipt.