Background India has an above global average, of both incidence and mortality, of head and neck cancer. Squamous cell carcinoma constitutes a majority of tumors in the head and neck region. The squamous cell carcinoma of head and neck (HNSCC) are heterogeneous depending on the subsite and have different underlying molecular features. like the gingivobuccal tumors are associated with habits like tobacco (chewing and smoking), and alcohol. Despite advancements in many areas of molecular sciences, the clinical practice in head and neck oncology services based on tumor location, histology and stage has not changed. The current solutions for patients with primary head and neck tumors remain as surgery (for oral cavity tumors with adjuvant radiotherapy or chemotherapy based on risk recurrence), radiotherapy (in the cases of oropharyngeal, hypopharyngeal and laryngeal tumors where organ preservation is needed) and concurrent chemotherapy (with cisplatin or other platinum derivatives) and radiation (for locoregionally advanced tumors). For recurrent and metastatic disease, currently platinum-based therapy is used as a first line therapy option. Despite the initial enthusiasm on Cetuximab (the monoclonal antibody against the epidermal growth factor receptor (EGFR), it has added very little value (very little value addition in terms of quality of life, OS or against radiotherapy alone) and had high toxicity. Recently, there are positive signs on the effectiveness of certain immunotherapy agents (PD-1 inhibitors like Nivolumab and Pembrolizumab). However, there has been very little advancement of any therapeutic molecules that are universally available and accessible to a large number of patients with head and neck tumors. ​ The human papilomavirus (HPV) prevalence in oropharyngeal tumors in certain geographies is very high. However, this has not been proved or published in a large cohort of Indian patients. HPV positive oropharyngeal tumors have good prognosis and there are practices where HPV positive tumors are down-staged. Unlike oropharyngeal tumors, the incidence of HPV in oral cavity tumors is low. We have shown this with multiple analytes and methods in a large cohort of oral cavity tumors (Palve et al., 2018). ​ Our Focus We are focused on three aspects of the science of head and neck cancer. First, cataloging the molecular determinants in Indian patients and understand signatures associated with specific habits. Second, building integrated machine learning and deep learning tools to identify metastatic and locoregionally recurrent HNSCC to aid patient management. Third, use molecular knowledge on different HNSCC to design diagnostic/prognostic/choice-of-therapy/patient follow-up tests for clinical use. To start with, we have focused on oral tongue tumors. Oral tongue squamous cell carcinoma (OTSCC) are interesting as the association of habits (chewing and smoking tobacco) are less associated than other subsites, like gingiobuccal tumors. Additionally, patients with OTSCC tend to be younger and the tumors tend to be more aggressive. ​ We have cataloged somatic single nucleotide variants (SNVs), copy number variants (CNVs), genes with varying expression, 5-mC changes in oral tongue tumors (Krishnan et al. 2016; Krishnan et al. 2015; Nair et al. 2015). We have devised machine learning tools to perform integrated analyses of molecular, clinical and epidemeological determinants to discover variants/genes that can be used as biomarkers for predicting metastatic/locoregionally recurrent tumors a priori (Krishnan et al. 2018). In another proof-of-concept study, in collaboration with Professor Shumpei Ishikawa's lab from the University of Tokyo, Japan, we have shown the utility of phytoextracts from neem (Azadirachta indica) to identify potential drug targets in head and neck cancer cell lines (Krishnan, Katoh et al. 2019).

1. ​Prediction of a plant intracellular metabolite content class using image-based deep learning. (2019). Category: Deep Learning with images bioRxiv Article​ ​ Authors: Neeraja M Krishnan and Binay Panda

Background From 1990s, from nearly 60 causative genes for rare diseases like for thalassemia and sickle cell anemia, the number rose to over 5000 genes by 2019. This was possible by the introduction of high-throughput sequencing technology and associated computational tools for gene discovery. Even for non-rare diseases, high-throughput sequencing has made inroad to the clinic, both for diagnosis and for disease management. Our lab has been interested in making analytical tools available to the clinic for diagnostic purposes. ​ Our Focus We are interested in using sequencing-based assays in the clinic for diagnosis of human diseases. Professor Graeme Black's lab of St. Mary's Hospital, Manchester University, UK, in collaboration with our lab, has shown the utility of next generation sequencing data, especially copy number variations, in the clinical diagnostics (Ellingford et al. 2016; Ellingford et al. 2017). Additionally, we also are interested in finding the causative gene(s) for some of the rare disorders in India.

1. Building Biofoundry India: Challenges and Path Forward, Synthetic Biology (2021). Category: Perspective Article Article Authors: Binay Panda and Pawan K. Dhar 2. The mutational landscape of early and typical onset oral tongue squamous cell carcinoma (2020). Category: Metaanalysis + Bioinformatics/Computational Biology of tumor data Article & Other info Authors: Benjamin R. Campbell, Zhishan Chen, Daniel L. Faden, Nishant Agrawal, Ryan J. Li, Glenn J. Hanna, Gopalakrishna Iyer, Arnoud Boot, Steven G. Rozen, Andre L. Vettore, Binay Panda, Neeraja M. Krishnan, Curtis R. Pickering, Jeffrey N. Myers, Xingyi Guo, Krystle A. Lang Kuhs 3. Functional Genomics Screen with Pooled shRNA Library and Gene Expression Profiling with Extracts of Azadirachta indicaIdentify Potential Pathways for Therapeutic Targets in Head and Neck Squamous Cell Carcinoma (2019). Category: Experimental Biology + Bioinformatics/Computational Biology of Cell line-derived data Article & Figures/Tables/Data Supplemental Information GEO Link ​ Authors: Neeraja M Krishnan, Hiroto Katoh, Vinayak Palve, Manisha Pareek, Reiko Sato, Shumpei Ishikawa, Binay Panda ​ 4. Detection of High-Risk Human Papillomavirus in Oral Cavity Squamous Cell Carcinoma Using Multiple Analytes and Their Role in Patient Survival (2018). ​ Category: Experimental Biology + Bioinformatics/Computational Biology of cancer data Article Figures/Tables/Data Supplements Authors: Vinayak Palve, Jamir Bagwan, Neeraja M Krishnan, Manisha Pareek, Udita Chandola, Amritha Suresh, Gangotri Siddappa, Bonne L James, Vikram Kekatpure, Moni A Kuriakose, Binay Panda ​ 5. A minimal set of internal control genes for gene expression studies in head and neck squamous cell carcinoma (2018). ​ Category: Experimental Biology + Bioinformatics/Computational Biology of cancer data Article & Figures/Tables/Data Supplemental Information Authors: Vinayak Palve, Manisha Pareek, Neeraja M Krishnan, Gangotri Siddappa, Amritha Suresh, Moni A Kuriakose, Binay Panda ​ 6. CAFE MOCHA: An Integrated Platform for Discovering Clinically Relevant Molecular Changes in Cancer; an Example of Distant Metastasis and Recurrence-linked Classifiers in Head and Neck Squamous Cell Carcinoma (2018). Category: Computational analysis of cancer data Article Figures/Tables/Data Supplements Authors: Neeraja M Krishnan, Mohanraj I, Janani Hariharan, Binay Panda ​ 7. Comparative analysis of venom-associated genes from an Old-World viper, Daboia russelii (2017). ​ Category: Original Research Article on Genome Sequencing and Analysis ​ Article & Figures/Tables/Data​ Supplemental Information SRA Link Authors: Neeraja M Krishnan and Binay Panda ​ 8. RNAtor: an Android-based application for biologists to plan RNA sequencing experiments. Category: Mobile App development for biologists Article Code Authors: Shruti Kane, Himanshu Garg, Neeraja M Krishnan, Aditya Singh, Binay Panda ​ 9. A Minimal DNA Methylation Signature in Oral Tongue Squamous Cell Carcinoma Links Altered Methylation with Tumor Attributes (2016). Category: Original Research Article on Integrated Genome Science and Analyses ​ Article Figures/Tables/Data GEO Data Authors: Neeraja M Krishnan, Kunal Dhas, Jayalakshmi Nair, Vinayak Palve, Jamir Bagwan, Gangotri Siddappa, Amritha Suresh, Vikram D Kekatpure, Moni A Kuriakose, Binay Panda 10. An integrated transcriptomics and proteomics study of Head and Neck Squamous Cell Carcinoma – methodological and analytical considerations (2016). Category: Sequential RNA and protein isolation from tumor tissues and Integrated Transcriptomics and Proteomics Analyses Article & Figures/Tables/Data ​ Authors: Anupama Rajan Bhat, Manoj Kumar Gupta, Priya Krithivasan, Kunal Dhas, Jayalakshmi Nair, Ram Bhupal Reddy, Sudheendra HV, Sandip Chavan, Harsha Vardhan, Sujatha Darsi, Lavanya Balakrishnan, Shanmukh Katragadda, Vikram Kekatpure, Amritha Suresh, Pramila Tata, Binay Panda, Moni A Kuriakose, Ravi Sirdeshmukh ​ 11. An Improved Genome Assembly of Azadirachta indica A. Juss. (2016). Category: Original Research Article on Genome Sequencing and Analyses ​ Article Figures/Tables/Data Supplemental Info FASTA Assembly Authors: Neeraja M Krishnan, Prachi Jain, Saurabh Gupta, Arun K Hariharan, Binay Panda 12. Molecular findings from 537 individuals with inherited retinal disease (2016). Category: Original Research Article on Clinical Genetics (Collaborative publication) ​ Article & Figures/Tables/Data ​ Authors: Jamie M Ellingford, Stephanie Barton, Sanjeev Bhaskar, James O'Sullivan, Simon G Williams, Janine A Lamb, Binay Panda, Panagiotis I Sergouniotis, Rachel L Gillespie, Stephen P Daiger, Georgina Hall, Theodora Gale, Christopher Lloyd, Paul N Bishop, Simon C Ramsden, Graeme C M Black ​ 13. Integrated analysis of oral tongue squamous cell carcinoma identifies key variants and pathways linked to risk habits, HPV, clinical parameters and tumor recurrence (2015). Category: Original Research Article on Integrated Genome Science and Analyses ​ Article & Figures/Tables/Data Methods / Scripts / Codes ​ Authors: Neeraja M Krishnan, Saurabh Gupta, Vinayak Palve, Linu Varghese, Swetansu Pattnaik, Prachi Jain, CosterwellKhyriem, Arun K Hariharan, Kunal Dhas, Jayalakshmi Nair, Manisha Pareek, Venkatesh K Prasad, GangotriSiddappa, Amritha Suresh, Vikram D Kekatpure, Moni A Kuriakose, Binay Panda ​ 14. Gene and miRNA expression changes in squamous cell carcinoma of larynx and hypopharynx (2015). Category: Original Research Article on Genome Science and Analyses ​ Article & Figures/Tables/Data Additional Files/Scripts Authors: Jayalakshmi Nair, Prachi Jain, Udita Chandola, Vinayak Palve, N R Harsha Vardhan, Ram Bhupal Reddy, Vikram D Kekatpure, Amritha Suresh, Moni A Kuriakose, Binay Panda 15. Role of the N6-methyladenosine RNA mark in gene regulation and its implications on development and disease (2014). Category: Review Article ​ Article ​ Authors: Udita Chandola, Radhika Das, Binay Panda ​ 16. SInC: An accurate and fast error-model based simulator for SNPs, Indels and CNVs coupled with a read generator for short-read sequence data (2014). Category: Software Article/Bioinformatics Tool Development ​ Article & Figures/Tables/Data Simulator Scripts/Codes Authors: Swetansu Pattnaik, Saurabh Gupta, Arjun A Rao, Binay Panda 17. A hybrid-computing environment for Burrows-Wheeler alignment for massive amount of short read sequence data (2014). Category: Software Article/Bioinformatics Tool Development ​ Article Scripts/Codes ​ Authors: Saurabh Gupta, Sanjoy Chaudhury, Binay Panda ​ 18. The Draft Genome and Transcriptome of Amaranthus hypochondriacus: A C4 Dicot Producing High-Lysine Edible Pseudo-Cereal (2014). Category: Original Research Article on Genome Science (Collaborative Publication) ​ Article & Figures/Tables SRA Link Supplemental Data Authors: Meeta Sunil, Arun K. Hariharan, Soumya Nayak, Saurabh Gupta, Suran R Nambisan, Ravi P Gupta, Binay Panda, Bibha Choudhary, Subhashini Srinivasan 19. Augmenting transcriptome assembly by combining de novo and genome-guided tools (2013). Category: Original Research Article on Bioinformatics Analysis ​ Article & Figures/Tables/Data Code/Scripts ​ Authors: Prachi Jain, Neeraja M Krishnan, Binay Panda ​ 20. Whither genomics diagnostics tests in India? (2012). Category: Editorial Commentary ​ Article ​ Author: Binay Panda ​ 21. COPS: A sensitive and accurate tool for detecting somatic copy number alterations using short-read sequence data from paired samples (2012). Category: Original Research Article on Bioinformatics Tool Development Article & Figures/Tables/Data Scripts/Codes Authors: Neeraja M Krishnan, Prakhar Gaur, Rakshit Chaudhary, Arjun A Rao, Binay Panda ​ 22. A Draft of the Genome and Four Transcriptomes of a Medicinal and Pesticidal Angiosperm Azadirachta indica (2012). Category: Original Research Article on Genome Science and Analyses ​ Article & Figures/Tables/Data SRA Link ​ Authors: Neeraja M Krishnan, Swetansu Pattnaik, Prachi Jain, Prakhar Gaur, Rakshit Choudhary, Srividya Vaidyanathan, S A Deepak, Arun K Hariharan, P G Bharath Krishna, Jayalakshmi Nair, Linu Varghese, Naveen K Valivarthi, Kunal Dhas, Krishna Ramaswamy and Binay Panda 23. Customisation of the exome data analysis pipeline using a combinatorial approach (2012). Category: Original Research Article on Bioinformatics Analysis Article & Figures/Tables/Data Scripts/Codes Authors: Swetansu Pattnaik, Srividya Vaidyanathan, Durgad G Pooja, S A Deepak, Binay Panda 24. De novo sequencing and assembly of Azadirachta indica fruit transcriptome (2011). Category: Original Research Article on Genome Science and Analyses ​ Article & Figures/Data SRA Link ​ Authors: Neeraja M Krishnan, Swetansu Pattnaik, S A Deepak, Arun K Hariharan, Prakhar Gaur, Rakshit Chaudhary, Prachi Jain, Srividya Vaidyanathan, P G Bharath Krishna, Binay Panda

1. Bioinformatics, High-throughput Biology, Systems Biology and Systems Medicine. In Genomic Medicine Principles and Practice, Second Edition, Oxford University Press, USA (2014). ISBN: 978-0-19-989602-84 (e-book), DOI: 10.1093/med/9780199896028.001.0001. 2. Big Data and Cancer. In "Big Data Analytics: Methods and Applications', Springer (2016). ISBN: 978-81-322-3628-3 (e-book), DOI: 10.1007/978-81-322-3628-3.

Background The introduction of high-throughput DNA sequencing technology along with proteomics and metabolomics experiments have revolutionized biological sciences in the last decade. Data from such large-scale experiments are interpreted at system’s level to understand the interplay among genome, transcriptome, epigenome, proteome, metabolome and regulome. With the race now shifting to make the process faster, cheaper and more accurate, the focus has been on the data. A disproportionately large amount of data generated using the high-throughput experiments is pushing biologists to collaborate with computer scientists, statisticians, and data scientists to get biological meanings out of the data. Therefore, the focus going forward is not going to be as much on data production, which still remains an important aspect of the discovery process, but on data analysis and biological interpretation of high-throughput data. Our Focus We work on building and optimizing tools for high-thrpughput data, especially data generated by DNA microarray and next-generation DNA sequencers. We have optmized and built computational tools for high-throughput r cancer genomics data (Pattnaik et al. 2012; Krishnan et al. 2012), for analysis of genome and design of transcriptome sequencing experiments (Kane et al. 2017; Jain et al. 2016). Additionally, we have built variant simulator for Illumina data (Pattnaik et al. 2014). Building and optimizing tools remain one of the ongoing activities in the lab.

Background Plant-derived secondary metabolites play a vital role in the food, pharmaceutical, agrochemical, and cosmetic industry. The current method of production of these metabolites is total organic synthesis, which is hugely time-consuming, expensive, slow, and yields a meagre amount. Synthetic biology using metabolic engineering, an approach to produce metabolites using microbes and yeast, has a real potential to change this. A successful example of the power of metabolic engineering is the production of the life saving anti-malarial drug, artemesinin. However, the pathways, meaning the exact sequence of events that happen in the living organisms to produce the secondary metabolites, are not always fully known. Therefore, the pathways and the enzymes involved in the key flux mediating steps have to be predicted before being engineered in microbes/yeast for bulk production. Azadirachtin, a secondary metabolite, is one of the many natural wonder chemicals and is derived from the seeds of a tropical tree, Azadirachta indica or neem that grows in the wild in India. Azadirachtin is extensively used in the agrochemical industry as insect and pest repellent and as an alternative to toxic chemicals. Additionally, it is used as a wound healer for burns and external infections, both in human and animals. Azadirachtin is obtained using organic extraction from the seeds of naturally grown trees collected by villagers over broad geography in India. Its concentration is measured using elaborate biochemistry and further analyses and is expensive. Additionally, its concentration often varies widely among plants, even within a small geographical area, making the process less efficient. A synthetic biology approach would make the entire extraction process plant-free and make azadirachtin available in bulk at an affordable price. As the current methods for azadirachtin extraction are expensive, requires extensive time, and access to expensive equipment, reagents, and specialized skills, developing easy-to-use and field based tools will help choose the correct trees for metabolite extraction. In long run, the metabolic engineering approach to synthetically produce the metabolite in bulk requires complete knowledge on its biosynthesis pathway(s), including the enzymes involved, will help solve the problem. Our Focus We were the 1st group in the world to completely sequence and assemble the genome and various organ-specific transcriptomes of a neem plant (Krishnan et al. 2011; Krishnan et al. 2012; Krishnan et al. 2016). This paved the way to identify and annotate novel genes in the neem plant, particularly those involved in the azadirachtin biosynthesis pathway. Taking this further, we are working on developing deep learning-based tools that can help fasten the understanding of pathway(s) for azadirachtin production. With an eventual goal to produce plant-free azadirachtin using microorganism/yeasts in the lab, we first developed imaging-based CNN models to identify trees that bear high azadirachtin in their seeds. This will provide relief to the industry in efficiently and cost-effectively choosing trees with higher amount of azadirachtin and using seeds only from those trees, making the entire process less random and cumbersome. Based on our invention, we have developed an easy-to-use mobile application (AZA classifier) that predicts real-time and can be used by any layperson in the field by capturing images of fruits and leaves of a neem plant (Krishnan et al. 2019).

1. The Global Cancer Genomics Consortium’s Second Annual Symposium, Genomics Medicine in Cancer Research. 2013 doi: 10.1177/1947601913484582 2. The Global Cancer Genomics Consortium’s First Annual Symposium: Interfacing Genomics and Cancer Medicine. Cancer Research. 2012. doi: 10.1158/0008-5472.CAN-12-1054

Popular Press (selected OpEds in National newspapers and online media) 1. Establishing India's Apple. The Hindu. Jan 22, 2022 2. Science and technology is central to strong and lasting Indo-US ties. Hindustan Times, Jul 26, 2021 3. Can India leverage data to conquer cancer? Hindustan Times, Jun 19, 2021 4. Did SARS-CoV-2 originate in a Chinese lab? OrissaPost, May 18, 2021 5. Our COVID-19 connection with the primitive caveman. The Hindu, May 01, 2021 6. Gene editing, the good first and then the worries. The Hindu, Oct 13, 2020 7. Testing for COVID-19 in India. The Hindu, Mar 31, 2020 8. Different peas in different pods. The Hindu, Sept 26, 2019 9. Connecting the dots with AI.The Hindu, Dec 30, 2018 ​ 10. How safe is CRISPR? The Hindu, Jul 29, 2018 ​ 11. Questions around raising the dead. The Hindu, Dec 31, 2017 ​​ 12. A March by Scientists. Confluence: Science, Scientists and Society.Confluence: Science, Scientists and Society. Dec 2017 ​ 13. The news and the noise about gene editing. The Hindu, Sun, Aug 06, 2017 ​ 14. Playing God. The Hindu, Sun, Jan 01, 2017 ​ 15. Human Genome Project: The ‘Write’ track. The Hindu, Sun, Jun 26, 2016 ​ 16. Will the Second Iteration of the Human Genome Project Usher in Greater Innovation? The Wire, Mon, June 20, 2016 17. Big data for a big country: Mind the gap. Nature India, May 31, 2016 ​ 18. Big Data for Complex Disorders: A Case in Point for Schizophrenia. The Wire, Sun, Feb 07, 2016 ​ 19. Betting big on big data. The Hindu, Sun, Jan 31, 2016 ​ 20. Not a Congress But a Big Fat Indian Science Wedding. The Wire, Fri, Jan 08, 2016 ​ 21. Back to the classroom. Indian Express, Tues, Nov 05, 2013

Background Biological diversity is threatened every day, mostly by human activities. Along with a rapid loss of habitat for most species in the wild and climate change, the threat to our biodiversity is real. Past work on habitat identification, taxonomy, species preservation through education, and artificial breeding and conservation biology have either stopped or slowed down the mass-extinction of some of the earth's life forms. Although essential, the real estimate of population structures, genetic diversity, genetic drift, evolution and adaptive variation, and demographic history is possible by using tools of Genome Science and Computational Biology. Decoding the genomes of various species and using markers across the genomes, one can provide more accurate estimations of the above parameters leading to informed decisions on conservation. Fortunately, rapid advances in genomics along with the availability of tools on DNA sequencing, bioinformatics, and computational biology, are making the above studies possible. Thus, a detailed understanding of the earth's biosphere by studying genomes of organisms and relating the genome information to their environments leading to their ecological restoration is now possible. Our focus India is home to rich biodiversity and with many important animal and plant species. Additionally, many of the plant species bear wide-ranging proven pharmaceutical and agrochemical properties. Several ancient texts describe their use against many human ailments. Additionally, understanding the genomes of the threatened animal species will help towards their conservation, spreading awareness, and design specific molecular assays to screening to stop illegal wildlife trade. We plan to do the sequencing of both important plant and animal species. Snake venoms have tremendous potential in developing new drugs and bioactive compounds. Additionally, snake venom genes and their products offer an excellent model system to study gene duplication, the evolution of regulatory DNA sequences, biochemical diversity, and novelty of venom proteins. Four snakes, Russell's viper (Daboia russelii), saw-scaled viper (Echis carinatus), spectacled cobra (Naja naja), and common krait (Bungarus caeruleus) are responsible for most snakebite-related mortality in India. Snake toxins are a mixture of complex chemicals, and their understanding will aid in not just reducing snakebite related deaths but potential development of novel antivenins. One of the challenges in studying the genomes of venomous animals is related to sample acquisition. Additionally, in India, Government permission is required to catch snakes and extract blood samples from them (all snakes are protected in India under the Indian Wildlife Protection Act, 1972). This may be partially circumvented by the use of shed skin that does not require drawing blood or taking any tissue from the animals. However, working with DNA isolated from shed skin has its own challenges. Microbial contamination, lack of full-length DNA in the shed skin cells, rapid degradation of DNA in humid conditions and computational challenges in dealing with short stretches of DNA are some of the bottlenecks for working with DNA from shed skin. Keeping the above in mind, we have optimized an experimental method to get high quality and large molecular weight DNA from freshly shed skin of snakes (Krishnan et al. 2017). The composition of snake venoms does not look just different among different species but also within the same species in India [36, 37]. Although the factors that give rise to the variation in the composition of the venom within a species is not well understood, it is believed that adaptation in response to the difference in diets are some of the factors that are responsible for the variation in the composition of venom. In a proof-of-concept study, we used the method and deduced the draft genome of Russell's viper (Daboia russelii) to perform comparative sequence analyses of putative toxin gene homologs using whole-genome sequencing data obtained from shed skin (Krishnan et al. 2017). In the next phase of our work, we would like to undertake the genomes and transcriptome sequencing, including from venom glands, assembly of the same snake species from different geographical locations in India at a very high coverage using multiple short- and long-read technologies and also using optical and Hi-C mapping. We shall also be working towards the understanding of venom gene evolution using genomes and transcriptomes from various organs, including from venom glands. This will enable us to understand genes responsible for envenomation and design better strategies to help come up with new therapeutic strategies against venomous snakebites.