Before going into scientific research, clarify these points,

1. What is the scientific question you will be addressing?
2. What will be the key finding that answer this question?
3. What will be the nature of the evidence you provide in support of your conclusion?
4. What are the three most recently published papers that are relevant to this question?
5. What significance do your results will have for the field?
6. What significance do your results will have for the broader community (of biologists and/or the public)?

Here are some global problems suggested by MIT.

Below are the important areas of biotechnology research. Try to find a supervisor who is working in these areas of field.

Genetic engineering

• Strategies for controlling gene expression
• Strategies for manipulating gene structure
• Strategies for gene containment

Large-scale approaches

• Technologies for analyzing gene function (e.g., arrays, SAGE)
• Technologies for analyzing gene structure/organization (e.g., molecular beacons)
• Chemogenomics or chemical genetics
• Pharmacogenomics/SNPs
• Computational analysis

Proteomics

• Technologies for analyzing/identifying protein structure/function (e.g., 2-D gels, mass spectrometry, yeast two-hybrid, SPR, NMR, arrays and chips)
• Structural genomics
• Computational analysis

Metabolomics

• Technologies for analyzing/profiling metabolites (chromatography, mass spectrometry)
• Computational analysis

Computational biology

• Bioinformatics; algorithms; data deconvolution
• Modeling and systems biology: kinetics-based models and constraints-based models

Molecular engineering

• Rational approaches for proteins/antibodies/enzymes/drugs
• Molecular evolution
• Molecular breeding approaches

Metabolic engineering

• Genetic manipulation of species of interest to modify or allow the production of a commercially or therapeutically relevant compound
• Computational analysis

Novel expression systems

• Mammalian cells
• Insect cells
• Bacteria
• Fungi
• Plant cells

Delivery of genes, drugs, or cells

• Targeting strategies
• Viral and nonviral vector strategies

Imaging

• Reporter molecules
• Imaging approaches/technologies for visualizing whole animals, cells, or single molecules
• Computational analysis

Nucleic acid therapeutics

• Gene therapy (targeting, expression, integration, immunogenicity)
• Antisense
• RNAi
• DNAzymes and ribozymes
• Other (e.g., chimeric oligonucleotides/triple helix)

Nanobiotechnology

• Nanomaterials for use in drug delivery or as therapeutics
• Nanomaterials for use in industrial biotechnology
• Nanosensors
• Nanosystems for imaging molecules and cells

Vaccines and applied immunology

• Antibody engineering
• T-cell therapies
• Therapies exploiting innate immunity (e.g. complement)
• Antigen delivery vectors and approaches
• Nucleic acid vaccines
• Computational analysis

Regenerative medicine

• Stem cells
• Tissue engineering
• Therapeutic cloning (somatic cell nuclear transfer)
• Xenotransplantation
• Biomaterials

Biosensors

• Approaches for detecting biological molecules
• Use of biological systems in detecting analytes

Assay systems

• Approaches for multiplexing and increasing throughput
• Selection/screening strategies for gene/proteins/drugs
• Microfluidics

Biomaterials

• Engineering materials for biological application
• Molecular imprinting
• Biomimetics
• Nanotechnology

Agbiotech and transgenic plants

• Crop improvement (resistance to stress, disease, pests)
• Nutraceuticals
• Forest biotechnology
• Plant vaccines
• Plants as bioreactors
• Gene-containment strategies

Pharming

• Transgenic animals
• Knockouts
• Reproductive cloning
• Biopharmaceutical and enzyme production
• Transgene targeting and expression strategies

Environmental

• Bioremediation
• Biomining
• Phytoremediation
• Monitoring