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Bioinformatics Internship

Join NTHRYS for a Bioinformatics Internship to explore the intersection of biology and computer science, focusing on data analysis, genomics, and computational biology.

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Bioinformatics Internship

Advanced Focused Areas for Interns in Bioinformatics Internships

Internships in 200+ fields

Info @ +91-7993084748
Fee as low as Rs 6000 / 10 Days Duration
Click Here for Application Process
Important Note
Note 1: Candidates may select any one of the focused areas listed below for their internship.
Note 2: Fundamental concepts are provided as guidance for candidates who require them; however, candidates may choose to bypass these sections if desired.
Note 3: All candidates will gain practical, hands-on experience with every step outlined in the provided methodology.
Note 4: Comprehensive placement assistance and career guidance will be available to all candidates during and after the internship.
Note 5: We understand that many students may lack basic practical exposure due to shortcomings in their college education. This is not the fault of the students but rather a failure of the institutions and their staff. At NTHRYS, our staff excel at training every student from the ground up, ensuring they gain the necessary skills and experience.
Back to All Internships Bioinformatics Internship Fee Details
  1. Sequence Alignment and Analysis
  2. Genome Annotation
  3. Phylogenetics and Evolutionary Analysis
  4. Protein Structure Prediction
  5. Comparative Genomics
  6. Functional Genomics
  7. Transcriptomics Data Analysis
  8. Metagenomics Data Analysis
  9. Proteomics Data Analysis
  10. Metabolomics Data Analysis
  11. Epigenomics Data Analysis
  12. Systems Biology
  13. Bioinformatics in Drug Discovery
  14. Bioinformatics in Personalized Medicine
  15. Biological Databases
  16. Biostatistics
  17. Computational Biology
  18. Biomarker Discovery
  19. Next-Generation Sequencing Data Analysis
  20. Bioinformatics in Cancer Research
  21. Genome-Wide Association Studies (GWAS)
  22. RNA-Seq Analysis
  23. Gene Expression Profiling
  24. Data Mining in Bioinformatics
  25. Machine Learning in Bioinformatics
  26. Network Biology
  27. Bioinformatics Algorithms and Software Development
  28. Molecular Dynamics Simulations
  29. Cheminformatics
  30. Bioinformatics in Agriculture
  31. Bioinformatics in Microbiology
  32. Computational Genomics
  33. Bioinformatics in Neuroscience
  34. Structural Bioinformatics
  35. Bioinformatics in Immunology
  36. Data Visualization in Bioinformatics
  37. Functional Annotation of Genomes
  38. Genome Editing Tools and Bioinformatics
  39. Bioinformatics and Genetic Epidemiology
  40. Metagenomic Sequence Analysis
  41. Bioinformatics in Metabolic Pathways
  42. Bioinformatics in Proteomics
  43. Gene Ontology Analysis
  44. Epigenetic Data Analysis
  45. Bioinformatics in Environmental Research
  46. Bioinformatics in Public Health
  47. Bioinformatics in Synthetic Biology
  48. Bioinformatics in Disease Pathways
  49. Bioinformatics in Virology
  1. Sequence Alignment and Analysis Topics

    Focuses on techniques for comparing DNA, RNA, and protein sequences to identify similarities and differences, including algorithms like BLAST, multiple sequence alignment, and phylogenetic tree construction.
  2. Genome Annotation Topics

    Studies the process of identifying and labeling the functional elements of a genome, such as genes, regulatory regions, and non-coding sequences, using computational tools and experimental data.
  3. Phylogenetics and Evolutionary Analysis Topics

    Explores the relationships between organisms based on genetic data, including the construction of phylogenetic trees, evolutionary models, and the study of speciation and divergence.
  4. Protein Structure Prediction Topics

    Focuses on computational methods for predicting the three-dimensional structure of proteins from their amino acid sequences, including homology modeling, ab initio methods, and molecular dynamics simulations.
  5. Comparative Genomics Topics

    Studies the similarities and differences in the genomes of different species, including the identification of conserved elements, gene families, and the evolutionary processes that shape genomes.
  6. Functional Genomics Topics

    Explores the relationship between genes and their functions, including the use of high-throughput technologies like RNA-Seq, ChIP-Seq, and CRISPR screens to study gene expression, regulation, and interaction networks.
  7. Transcriptomics Data Analysis Topics

    Focuses on the analysis of transcriptomic data, including the quantification of gene expression levels, identification of differentially expressed genes, and the study of alternative splicing and gene regulation.
  8. Metagenomics Data Analysis Topics

    Studies the analysis of metagenomic data, including the identification and classification of microorganisms in environmental samples, functional annotation of microbial genes, and the study of microbial communities.
  9. Proteomics Data Analysis Topics

    Focuses on the computational analysis of proteomics data, including protein identification, quantification, and the study of post-translational modifications and protein-protein interactions.
  10. Metabolomics Data Analysis Topics

    Studies the analysis of metabolomics data, including the identification and quantification of metabolites in biological samples, pathway analysis, and the integration of metabolomics with other omics data.
  11. Epigenomics Data Analysis Topics

    Focuses on the study of epigenetic modifications across the genome, including DNA methylation, histone modification, and chromatin accessibility, and their roles in gene regulation and disease.
  12. Systems Biology Topics

    Explores the integration of different types of biological data to model and understand complex biological systems, including the study of gene regulatory networks, metabolic pathways, and cellular processes.
  13. Bioinformatics in Drug Discovery Topics

    Studies the application of bioinformatics in identifying new drug targets, predicting drug efficacy and toxicity, and designing novel therapeutics, including the use of computational docking and virtual screening.
  14. Bioinformatics in Personalized Medicine Topics

    Focuses on the use of bioinformatics to tailor medical treatment to individual patients based on their genetic, transcriptomic, and proteomic data, including the identification of biomarkers and the prediction of drug response.
  15. Biological Databases Topics

    Explores the development and management of databases for storing, retrieving, and analyzing biological data, including genomic, proteomic, and metabolomic information, and the challenges of big data in biology.
  16. Biostatistics Topics

    Focuses on the application of statistical methods to the analysis of biological data, including the design of experiments, hypothesis testing, and the interpretation of results in genomics, proteomics, and clinical trials.
  17. Computational Biology Topics

    Studies the development and application of mathematical models, algorithms, and computational techniques to analyze and interpret biological data, including the modeling of biological systems and the simulation of cellular processes.
  18. Biomarker Discovery Topics

    Focuses on the identification of biological markers for disease diagnosis, prognosis, and treatment, including the use of genomic, proteomic, and metabolomic data to discover and validate new biomarkers.
  19. Next-Generation Sequencing Data Analysis Topics

    Explores the analysis of data generated by next-generation sequencing technologies, including the alignment of reads, variant calling, and the study of genetic variation, gene expression, and epigenetic modifications.
  20. Bioinformatics in Cancer Research Topics

    Studies the application of bioinformatics in understanding cancer biology, including the analysis of genomic, transcriptomic, and epigenomic data to identify cancer drivers, biomarkers, and therapeutic targets.
  21. Genome-Wide Association Studies (GWAS) Topics

    Focuses on the identification of genetic variants associated with complex traits and diseases using large-scale genomic data, including the analysis of single nucleotide polymorphisms (SNPs) and the interpretation of GWAS results.
  22. RNA-Seq Analysis Topics

    Explores the analysis of RNA-Seq data to study gene expression, transcript diversity, and alternative splicing, including the quantification of transcripts, differential expression analysis, and the integration of RNA-Seq data with other omics data.
  23. Gene Expression Profiling Topics

    Focuses on the analysis of gene expression data to identify differentially expressed genes, study gene regulatory networks, and understand the molecular mechanisms underlying diseases and biological processes.
  24. Data Mining in Bioinformatics Topics

    Studies the application of data mining techniques to extract meaningful patterns and knowledge from large biological datasets, including the use of clustering, classification, and association rule mining in genomics and proteomics.
  25. Machine Learning in Bioinformatics Topics

    Explores the use of machine learning algorithms to analyze and interpret biological data, including the development of predictive models for gene expression, disease classification, and drug response prediction.
  26. Network Biology Topics

    Focuses on the study of biological networks, including gene regulatory networks, protein-protein interaction networks, and metabolic networks, and their roles in understanding complex biological systems and diseases.
  27. Bioinformatics Algorithms and Software Development Topics

    Studies the design and implementation of algorithms and software tools for analyzing biological data, including sequence alignment, gene prediction, and structural biology, and the development of user-friendly interfaces for bioinformatics applications.
  28. Molecular Dynamics Simulations Topics

    Explores the use of molecular dynamics simulations to study the behavior of biological molecules at the atomic level, including protein folding, ligand binding, and the dynamic properties of biomolecular systems.
  29. Cheminformatics Topics

    Focuses on the application of computational techniques to analyze chemical data, including the design of drug-like molecules, virtual screening, and the study of chemical properties and interactions with biological targets.
  30. Bioinformatics in Agriculture Topics

    Studies the application of bioinformatics to agricultural research, including the analysis of crop genomes, the study of plant-microbe interactions, and the development of bioinformatics tools for improving crop yield and resistance to diseases.
  31. Bioinformatics in Microbiology Topics

    Explores the use of bioinformatics in studying microbial genomes, metagenomics, and microbial communities, including the identification of pathogenic microbes, antibiotic resistance genes, and microbial interactions in various environments.
  32. Computational Genomics Topics

    Focuses on the development and application of computational methods for analyzing genomic data, including the study of genome organization, gene regulation, and the identification of genetic variants associated with diseases.
  33. Bioinformatics in Neuroscience Topics

    Studies the application of bioinformatics to neuroscience research, including the analysis of genomic, transcriptomic, and epigenomic data to understand brain function, neural development, and neurodegenerative diseases.
  34. Structural Bioinformatics Topics

    Explores the study of the three-dimensional structures of biological molecules, including the prediction of protein structures, the analysis of protein-ligand interactions, and the use of structural data in drug design and molecular biology.
  35. Bioinformatics in Immunology Topics

    Focuses on the use of bioinformatics to study the immune system, including the analysis of immune repertoire sequencing, the prediction of antigenic peptides, and the identification of immune-related genes and pathways.
  36. Data Visualization in Bioinformatics Topics

    Studies the development and application of visualization tools for representing complex biological data, including the use of graphical interfaces, interactive plots, and data integration platforms for genomics, proteomics, and systems biology.
  37. Functional Annotation of Genomes Topics

    Focuses on the identification and characterization of functional elements in genomes, including the annotation of coding and non-coding regions, regulatory elements, and the integration of functional genomics data with genome sequences.
  38. Genome Editing Tools and Bioinformatics Topics

    Explores the integration of bioinformatics with genome editing technologies, including CRISPR-Cas systems, the design of guide RNAs, and the prediction of off-target effects and functional outcomes of genome modifications.
  39. Bioinformatics and Genetic Epidemiology Topics

    Studies the application of bioinformatics in understanding the genetic basis of diseases in populations, including the analysis of genetic association studies, the identification of risk alleles, and the study of gene-environment interactions.
  40. Metagenomic Sequence Analysis Topics

    Focuses on the analysis of metagenomic sequences to study microbial diversity, identify functional genes in microbial communities, and understand the ecological roles of microbes in various environments.
  41. Bioinformatics in Metabolic Pathways Topics

    Explores the computational analysis of metabolic pathways, including the reconstruction of metabolic networks, the prediction of enzyme functions, and the study of metabolic flux in different organisms.
  42. Bioinformatics in Proteomics Topics

    Focuses on the use of bioinformatics tools to analyze proteomic data, including the identification of proteins, the study of post-translational modifications, and the integration of proteomics with other omics data.
  43. Gene Ontology Analysis Topics

    Studies the use of Gene Ontology (GO) terms to annotate and classify gene functions, including the analysis of GO enrichment in gene sets, the study of biological processes, and the functional annotation of genomic data.
  44. Epigenetic Data Analysis Topics

    Focuses on the computational analysis of epigenetic data, including DNA methylation, histone modifications, and chromatin accessibility, and their roles in gene regulation, development, and disease.
  45. Bioinformatics in Environmental Research Topics

    Studies the application of bioinformatics in understanding environmental processes, including the analysis of microbial communities, the study of biogeochemical cycles, and the impact of environmental changes on biodiversity.
  46. Bioinformatics in Public Health Topics

    Focuses on the use of bioinformatics to address public health challenges, including the study of infectious disease outbreaks, the identification of pathogen genomes, and the analysis of epidemiological data.
  47. Bioinformatics in Synthetic Biology Topics

    Explores the integration of bioinformatics with synthetic biology, including the design of synthetic gene circuits, the modeling of biological systems, and the development of computational tools for engineering biological functions.
  48. Bioinformatics in Disease Pathways Topics

    Studies the use of bioinformatics to understand the molecular pathways involved in diseases, including the identification of key genes and proteins, the reconstruction of disease networks, and the prediction of therapeutic targets.
  49. Bioinformatics in Virology Topics

    Focuses on the application of bioinformatics in the study of viruses, including the analysis of viral genomes, the identification of viral-host interactions, and the development of antiviral strategies based on genomic data.

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Note: Interns get complete handson exposure to all steps in the allocated methodology.
Fee, Application Process and Other Details: Please visit NTHRYS Internship Program Fees

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