Anand Singh Rathore

I'm Designer

I am a doctoral researcher at the Indraprastha Institute of Information Technology Delhi (IIIT-Delhi), working under the supervision of Prof. Gajendra P.S. Raghava. I hold a master’s degree in Zoology (2020–2022) and have since transitioned into the field of Data Science, driven by the transformative potential of Machine Learning and Artificial Intelligence. My current research focuses on peptide-based therapeutics, particularly exploring their druggability using computational approaches. Computational Biology, being a multidisciplinary field, allows for innovation at the intersection of biology, data science, and artificial intelligence. This fusion offers vast research opportunities to address complex biological challenges and advance therapeutic development.

Zoologist Turned Computational Biologist

Exploring the crossroads of biology and computation to unlock new possibilities in precision medicine and therapeutic design.

I actively work on building and deploying machine learning pipelines for bioinformatics applications such as toxicity prediction, motif analysis, and peptide screening. My toolkit spans Python, R, shell scripting, and technologies like BLAST, IEDB, SwissProt, and ESM-based models. I’m also exploring the frontiers of Quantum Machine Learning and Explainable AI to make bioinformatics models more transparent and insightful. My journey is driven by curiosity, interdisciplinary collaboration, and a desire to make meaningful contributions to biomedical research.

Technical Expertise

A curated showcase of my core competencies in computational biology and data science

Programming & Development

Python ML/DL R PHP HTML/CSS Databases

AI & Machine Learning

LLMs Explainable AI Scikit-learn / TensorFlow/ Quantum ML Data Visualization Dimensionality Reduction Model Interpretability ESM Models

Bioinformatics Tools

BLAST IEDB PSSM Profiling SwissProt Biopython Open Babel/ p2smi/ PepSMI PyMOL/ PDB MEGA

Resume

Research scholar in Computational Biology with strong academic background, practical laboratory training, and diverse experience in machine learning, proteiomics, genomics, and bioinformatics.

Education

Ph.D. in Computational Biology (Pursuing)

2022 – Present

Indraprastha Institute of Information Technology (IIIT-Delhi), India

Working under the supervision of Prof. (Dr) GPS Raghava on machine learning applications in peptide-based therapeutics.

M.Sc. in Zoology

2020 – 2022

Hansraj College, University of Delhi, Delhi, India

CGPA: 7.3

Acquired in-depth knowledge in animal physiology, animal endocrinology, molecular biology, developmental biology, and immunology. Gained hands-on experience with biological techniques such as microscopy, gel electrophoresis, and basic bioinformatics tools.

B.Sc. in Life Sciences

2017 – 2020

Sriyut College, APS University, Rewa, Madhyapradesh, India

Percentage: 72.33%

Built a strong foundation in cell biology, genetics, biochemistry, and microbiology. Developed analytical and laboratory skills, and was introduced to research methodologies and scientific writing.

Achievements

CSIR-UGC NET JRF

June 2022

All India Rank: 79 (Percentile: 99.67)

DBT-JRF

2022

Qualified under Category-I

GATE XL

2021

All India Rank: 409 | Score: 598

GATE BT

2022

All India Rank: 906 | Score: 454

Research & Lab Experience

Hands-on Laboratory Training

Jul – Sep 2021

Prof. Neeta Sehgal's Lab, Dept. of Zoology, University of Delhi

  • Agarose Gel Electrophoresis, SDS-PAGE, PCR, RNA Isolation
  • Western Blotting, Real-Time PCR, DNA & Protein Purification

Antimicrobial Peptide & Database Learning

Sep – Dec 2021

Under Asst. Prof. Vikash Sood, Jamia Hamdard

  • Peptide data extraction, Venn diagrams, Heatmaps, Clustering

In Silico Biology Virtual Internship

Sep 2021

Under Dr. Shobhana Manoharan, Biosrishti

  • BLAST, FASTA, Phylogenetics, Protein Docking (PatchDock, AutoDock)
  • Structure Prediction (Phyre2, SOPMA), Visualization (Chimera, RasMol)

Workshops & Conferences

IEDB Virtual User Workshop

La Jolla Institute for Immunology, USA

Python for Biology Workshop

INSCR 2021

International Conferences

Participated in conferences focusing on Cancer Biology, Nanomedicine, and Genomics

Certifications

(Meta) Genomics & Bioinformatics

Phixgen Pvt. Ltd.

Immunological Techniques

BCAS, University of Delhi

Secured First Merit Position

Publications

Peer-reviewed research articles, preprints, and scientific contributions showcasing our work in computational biology and bioinformatics.

Published Articles

Chemical Research in Toxicology

Hemolytik2: An Updated Database of Hemolytic and Non-hemolytic Peptides

Ayushi S et al.
2026 Published DOI
Communications Biology

Prediction of hemolytic peptides using machine learning approaches

Rathore AS et al.
2025 Published DOI
Protein Science

NTxPred2: A large language model for predicting neurotoxins

Rathore AS et al.
2025 Published DOI
Computers in Biology and Medicine

ToxinPred 3.0: An improved method for predicting toxicity of peptides and proteins

Rathore AS et al.
2024 Published DOI
Frontiers in RNA Research

Compilation of resources on subcellular localization of RNA

Chaudhary S et al.
2024 Published DOI
Heliyon

Antiprotozoal peptide prediction using machine learning approaches

Periwal N et al.
2024 Published DOI

Preprints

bioRxiv

A PLM-Based Method for Predicting Protein Ion Channel Modulators for Drug Discovery and Safety Evaluation

Rathore AS et al.
2025 Preprint DOI
arXiv

MAP format for representing chemical structures as text for large language models

Shendre A et al.
2025 Preprint DOI
q-Bio.BM

Webservers

This section showcases a collection of web-based resources and tools developed to facilitate peptide-based therapeutic research. These include predictive models, curated databases, and computational methods for analyzing bioactive peptides.

  • All
  • Tool
  • Database
  • Method
  • Review
  • Book Chapter

Tool

Method for prediction toxicity of peptides

Tool

Antiprotozoal peptide prediction using machine learning with effective feature selection techniques

Method

MAP Format for Representing Chemical Modifications, Annotations, and Mutations in Protein Sequences: An Extension of the FASTA Format

Tool

Prediction of hemolytic peptides and their hemolytic concentration

Database

Hemolytik2: An Updated Database of Hemolytic Peptides and Proteins

Review

Compilation of resources on subcellular localization of lncRNA

Tool

NTxPred2: A large language model for predicting neurotoxic peptides and neurotoxins

Tool

IonNTxPred: LLM-based Prediction and Designing of Ion Channel Impairing Proteins

Books

Coming Soon...

Research Areas

My research spans a variety of domains in bioinformatics, computational biology, and artificial intelligence to address challenges in health and life sciences.

Machine Learning in Bioinformatics

Development of predictive models for biological data using supervised and unsupervised learning techniques.

Peptide Therapeutics

Design and prediction of therapeutic peptides for antimicrobial, anticancer, and hemolytic activities.

Toxin and Allergen Prediction

Computational tools for the identification of toxic and allergenic proteins and peptides.

Vaccine Informatics

Epitope mapping and computational vaccine design using immunoinformatics approaches.

AI for Precision Medicine

Leveraging artificial intelligence for personalized diagnosis and treatment strategies.

Web Server and Tool Development

Creating user-friendly, freely available web interfaces and software tools for the scientific community's access to predictive models.

Genomics and Sequence Analysis

Exploration of genomic datasets to uncover gene functions, mutations, and their role in disease and evolution.

My Contributions

Impact-driven work spanning knowledge creation, mentorship, community building, and societal advancement through computational biology.

Generation of Knowledge

Developed advanced machine learning and transformer-based models for peptide toxicity prediction, enabling safer therapeutic design.

Dataset Curation
Hybrid Frameworks
Accessible Tools
Research Innovation

Mentorship & Teaching

Guided students in biomedical machine learning courses and research methodology, fostering analytical skills and collaborative spirit.

Course Leadership
Content Creation
Individual Mentoring
Education

Community Building

Promoted open science through resource sharing, interdisciplinary collaboration, and active participation in scientific discourse.

Open-Source Tools
Conference Engagement
Collaborative Projects
Open Science

Societal Impact

Created accessible computational tools for safer peptide therapeutics, advancing public health objectives through open science.

Therapeutic Safety
Open Access
Biomedical Pipeline
Public Health

Cumulative Impact

5+
ML Models Developed
50+
Students Mentored
100%
Open Access Tools
7+
Interdisciplinary Projects

Contact

Feel free to reach out with any questions or collaboration ideas.

Address

A318 R & D Building, IIIT-Delhi

Call

+91 8819919830

Email

anandr@iiitd.ac.in

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