Please check Computational biology Internship details below.
Click Here to View Computational biology Internship Program Structure
Traversing Diverse Computational biology Research Horizons: Specialized Research Methodologies and Varied Topics Unveiled
Research Methodologies focussed for Internship students under Computational biology:
NTHRYS Computational Biology Internship Focussed Research Areas
- Algorithm Development: Create novel computational algorithms for analyzing biological data, such as gene expression patterns, protein interactions, or genomic sequences, to improve accuracy and efficiency.
- Predictive Modeling: Develop predictive models using machine learning and statistical techniques to forecast biological phenomena like protein folding, drug-target interactions, or disease progression.
- Network Analysis: Investigate complex biological networks (e.g., metabolic, regulatory, or protein-protein interaction networks) to identify key nodes, pathways, and their implications in cellular processes.
- Genome Annotation: Improve methods for annotating and interpreting genomic data, aiming to understand gene function, regulatory elements, and variations across different species.
- Structural Biology Simulations: Utilize computational methods like molecular dynamics simulations to study the structure, dynamics, and interactions of biomolecules (proteins, RNA, DNA) for drug discovery or functional insights.
- Evolutionary Analysis: Explore evolutionary patterns and mechanisms using computational approaches to understand the origins of genetic variation, speciation events, and molecular adaptation.
- Systems Biology Integration: Integrate multi-omics data (genomics, transcriptomics, proteomics, metabolomics) to create comprehensive models describing the interplay of biological components in living systems.
- Drug Design and Discovery: Develop computational tools to facilitate drug design, virtual screening of compounds, and prediction of drug-target interactions, expediting the drug discovery process.
- Personalized Medicine: Use computational methods to analyze individual genomic data, aiming to tailor medical treatments, predict disease risk, and optimize therapies based on genetic profiles.
- Biological Data Visualization: Create intuitive and informative visualization tools to aid researchers in interpreting complex biological data, facilitating data-driven insights and hypothesis generation.
- Single-cell Analysis: Develop computational methods to analyze and interpret single-cell sequencing data, unraveling cellular heterogeneity and dynamics in tissues and organisms.
- Cancer Genomics: Investigate computational approaches to characterize tumor heterogeneity, identify driver mutations, and predict treatment responses in cancer patients based on genomic data.
- Metagenomics: Develop tools and algorithms to analyze metagenomic data from environmental samples or microbiomes, exploring microbial diversity, function, and their impact on ecosystems or human health.
- RNA Structure Prediction: Improve computational methods for predicting RNA secondary and tertiary structures, understanding their functional implications in gene regulation and disease.
- Phylogenetics and Phylogenomics: Develop advanced algorithms to reconstruct evolutionary relationships among species, leveraging genomic data to infer phylogenetic trees and evolutionary histories.
- Spatial Transcriptomics: Develop computational techniques to analyze spatially resolved transcriptomic data, elucidating cellular interactions and organization within tissues.
- Epigenomics Analysis: Create tools for analyzing epigenetic modifications (DNA methylation, histone modifications) to understand their role in gene regulation, development, and diseases.
- Immunoinformatics: Use computational methods to analyze immune system data, such as antigen recognition, immune cell receptors, and immune response modeling, aiding in vaccine design and immunotherapy.
- Multi-scale Modeling: Integrate computational models across different scales of biological organization (molecular, cellular, tissue, organismal) to gain a holistic understanding of biological systems.
- Biological Image Analysis: Develop algorithms for processing and analyzing biological images (microscopy, medical imaging) to extract quantitative information about cellular structures and functions.
- Artificial Intelligence in Biology: Explore the applications of AI, including deep learning and neural networks, in analyzing biological data, predicting biological activities, and optimizing experimental design.
- Evolutionary Developmental Biology (Evo-Devo): Employ computational approaches to study the genetic and developmental basis of evolutionary changes in organismal structures and developmental processes.
- Disease Biomarker Discovery: Use computational methods to identify and validate biomarkers associated with various diseases, aiding in early diagnosis and prognosis prediction.
- Comparative Genomics: Compare genomic data across species to identify conserved elements, understand evolutionary constraints, and uncover functional elements in genomes.
- Population Genetics: Develop computational models to study genetic variation within and between populations, exploring factors like migration, selection, and demographic history.
- Biomedical Text Mining: Create algorithms to extract and analyze information from biomedical literature, aiding in knowledge discovery and facilitating data-driven research.
- Environmental Genomics: Apply computational tools to analyze genomic data from environmental samples, understanding microbial ecology, biodiversity, and ecological interactions.
- Neuroinformatics: Develop computational tools to analyze complex neural data (neuroimaging, neuronal activity), aiming to understand brain function, disorders, and cognitive processes.
- Bioinformatics Education and Outreach: Develop educational resources and tools to enhance bioinformatics literacy among researchers, students, and the broader community.
Fee Strctures for Computational Biology Internship:
Please scroll down to view Application Process
Fee Reduction Chances:
- Group Reductions: Given for all durations for students who are joining in a group of 4 and above. There will be a considerable reduction given on total fee per head. Contact on below given number.
- Early Bird Reductions: Given for all students who are registering minimum three months before joining date. There will be 20% reduction given on total fee. Contact on below given number.
- MoU Reductions: Given for all students who are joining from institutions which has MoU with NTHRYS BIOTECH LABS will. There will be considerable reduction given on total fee. Contact on below given number.
- Toppers Reduction: Given for 3 months and above durations for all students who are top rankers in their institutions. Students can request fee reduction with the help of the head of institution (Principal, Not HOD) from the principals official email id. Contact on below given number.
- Economically Backward Class Reductions: Given for all durations to all students belonging to economically backward class can request for fee reduction. Contact on below given number.
Important Note: Candidates may apply only one type of reduction from the aforementioned list at any given time.
Contact via whatsapp on +91 - 9014935156 for reduction details.
Application Process
Note: Please cross confirm your selected slot's full fee and registration fee via whatsapp on +91-7993084748 or +91-9014935156.
- Reg Fee payment screenshot / photocopy (Paid via "Pay Reg Fee" button available on "Fee" tab
- Any ID Card Photocopy
- Draft an email with 1, 2 as attachments, provide Postal Address along with parents name and pincode, and email id, mobile number and joining date.
- Send the above drafted mail to counselor.bio ( a t ) nthrys.com
- Update about the email as well as send payment screenshot / photocopy via whatsapp on +91-7993084748
- Our Academic Services department will confirm the application with in 10 mins to 1 hour.
Testimonials
VB. Bhavana View on Google
I have completed my 6 month dissertation in NTHRYS biotech labs. The lab is adequately equipped with wonderful, attentive and receptive staff. It is a boon to the students venturing into research as well as to students who would like to garner lab exposure. I had a pleasant experience at NTHRYS thanks to Balaji S. Rao Sir for his constant support, mettle and knowledge. I would also like to give special regards to Zarin Mam for teaching me the concepts of bioinformatics with great ease and for helping me in every step of the way. I extend my gratitude to Vijaya Mam, and Sindhu Mam for helping me carry out the project smoothly.
Durba C Bhattacharjee View on Google
I have just completed hands on lab trainings at NTHRYS in biotechnology which includes microbiology, molecular and immunology and had gained really very good experience and confidence having good infra structures with the guidance of Sandhya Maam and Balaji Sir.
Recommending to any fresher of biotechnology or microbiology field who wants to be expert before joining to
related industry.
Razia View on Google
Best place to aquire and practice knowledge.you can start from zero but at the end of the internship you can actually get a job that is the kind of experience you get here.The support and encouragement from the faculty side is just unexplainable because they make you feel like family and teach you every bit of the experiment.I strongly recommend NTHRYS Biotech lab to all the students who want to excel in their career.
Srilatha View on Google
Nice place for hands on training
Nandupandu View on Google
Very good place for students to learn all the techniques
Sadnaax View on Google
I apprenticed in molecular biology and animal tissue culture, helped me a lot for my job applications. Sandhya and Balaji sir were very supportive, very helpful and guided me through every step meticulously. Helped me learn from the basics and helped a lot practically. The environment of the lab is very hygienic and friendly. I had a very good experience learning the modules. Would recommend
Shivika Sharma View on Google
I did an internship in NTHRYS under Balaji sir and Sandhya maam. It was a magnificent experience. As I got hands-on experience on practicals and I was also provided with protocols and I learned new techniques too.This intership will help me forge ahead in life. The staff is very supportive and humble with everyone. Both sir and maam helped me with my each and every doubts without hesitation.
Digvijay Singh Guleria View on Google
I went for 2 months for different training programs at NTHRYS Biotech, had a fun learning experience. Everything was hands-on training and well organised protocols. Thank you Balaji sir and Sandhya mam for this life time experience.
Anushka Saxena View on Google
I’m a biotechnology student from Dy patil University mumbai and I recently completed my 6 months dissertation project at Nthrys Biotech Labs in Hyderabad. I had a great experience and I would highly recommend this lab to other students as well .
The first thing that I appreciated about Nthrys Biotech Labs was the friendly and supportive environment. Balaji sir and the staff Ragini and Sandhya ma’am were always willing to help me and they were always patient with my questions.
I also felt like I was part of a team and that I was making a real contribution to the companys research.
I learned a lot during my dissertation at Nthrys Biotech Labs not only academically but also personally . I had the opportunity to work on a variety of projects, which gave me a broad exposure to the field of biotechnology. I also learned a lot about the research process and how to conduct experiments.
In addition to the technical skills that I learned, I also developed my soft skills during my internship. I learned how to communicate effectively, how to work independently, and how to work as part of a team.
Overall, I had a great experience at Nthrys Biotech Labs and I would highly recommend this company to other students.
Once again I would like to render a big thank you to Balaji Sir and Vijayalakshmi ma’am for imbibing with all the knowledge along with helping me publish my research paper as well and its all because of them I scored unbelievably well in my final semester.
Nithin Pariki View on Google
Lab equipment and protocols are good, it gives good hands on experience for freshers.
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