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Week - 1 |
Scientific Reasoning and Experimental Approaches in Molecular Biology
Content:
• Basic steps of scientific research
• Experimental thinking in molecular biology
• Relationship between observation, problem, research question, and hypothesis
• Basic research, translational research, and clinical research
• Causality, association, and correlation in experimental studies
• Common experimental errors in molecular biology studies
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Week - 2 |
Developing a Research Question and Literature Review
Content:
• Characteristics of a strong research question
• Identification of research gaps
• Literature search strategies
• PubMed, Google Scholar, Web of Science, Scopus, and preprint sources
• Selection of keywords and search strategies
• Developing a hypothesis based on current literature
• Making the research question original and testable
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Week - 3 |
Hypothesis Formulation, Aim, and Objectives
Content:
• What is a hypothesis?
• Null hypothesis and alternative hypothesis
• Main hypothesis and sub-hypotheses
• Writing the general aim and specific objectives
• Alignment between research question, hypothesis, and experimental design
• Hypothesis development using molecular biology examples
• Transforming a hypothesis into measurable experimental outcomes |
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Week - 4 |
Variables, Controls, and Experimental Groups
Content:
• Dependent, independent, and controlled variables
• Confounding variables
• Positive control, negative control, and vehicle control
• Technical control and biological control
• Housekeeping genes, loading controls, and internal controls
• Formation of experimental groups
• Selection of controls in cell culture, PCR, Western blot, ELISA, and sequencing studies
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Week - 5 |
Sample Selection, Experimental Replication, and Statistical Power
Content:
• Effect of sample selection on experimental reliability
• Biological replicates and technical replicates
• Principles of randomization and blinding
• Balance and comparability among experimental groups
• Concept of sample size
• Effect size, variation, and statistical power
• Impact of low sample size on molecular biology experiments
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Week - 6 |
Experimental Planning in Molecular Biology
Content:
• Designing an experimental workflow
• Preparing timelines and experimental matrices
• Passage number, confluency, and dose–time design in cell culture experiments
• Experimental planning for gene expression analyses
• Sample preparation and comparison strategies in protein analyses
• Quality control steps in nucleic acid-based experiments
• Planning pilot experiments before full-scale studies
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Week - 7 |
Data Collection, Data Organization, and Laboratory Records
Content:
• Raw data, processed data, and analyzed data
• Principles of laboratory notebook keeping
• File naming and data archiving
• Concept of experimental metadata
• Excel, GraphPad Prism, R, and basic data organization approaches
• Organization of imaging data, numerical data, and sequencing data
• Prevention of data loss, data mixing, and recording errors
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Week - 8 |
Basic Statistical Approaches and Data Analysis
Content:
• Descriptive statistics
• Mean, median, standard deviation, and standard error
• Concept of normal distribution
• Introduction to parametric and non-parametric tests
• Two-group comparisons
• Multiple-group comparisons
• Correlation and regression
• p-value, confidence interval, and effect size
• Selection of statistical tests for molecular biology data
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Week - 9 |
Data Visualization and Scientific Figure Preparation
Content:
• Types of scientific graphs
• Use of bar graphs, scatter plots, box plots, violin plots, and line graphs
• Correct presentation of error bars
• Displaying biological replicates in graphs
• Visualization of statistical significance
• Presentation of microscopy, Western blot, and gel images
• Avoiding misleading graphical representations
• Principles of publication-quality figure preparation
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Week - 10 |
Data Interpretation and Biological Meaning
Content:
• Difference between statistical significance and biological significance
• Relating results to the hypothesis
• Interpretation of expected and unexpected results
• Evaluation of experimental error sources
• Developing alternative explanations
• Scientific value of negative results
• Building molecular mechanisms and proposing models
• Comparing results with the literature
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Week - 11 |
Reproducibility, Reliability, and Data Integrity
Content:
• Concepts of repeatability and reproducibility
• Sources of experimental variation
• Batch effects and technical biases
• Protocol standardization
• Storage and accessibility of raw data
• Data manipulation, selective data use, and cherry-picking
• Integrity of image-based data
• Open science, data sharing, and preregistration
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Week - 12 |
Structure of a Scientific Manuscript and the Writing Process
Content:
• Main sections of a scientific manuscript
• Title, abstract, and keywords
• Writing the introduction section
• Level of detail in the materials and methods section
• Presenting data in the results section
• Interpretation and limitations in the discussion section
• Writing the conclusion section
• Journal selection and manuscript preparation according to the target journal
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Week - 13 |
Authorship Criteria, Plagiarism, Citation, and Publication Ethics
Content:
• Authorship criteria
• Author order and contribution statements
• Acknowledgements and non-author contributions
• Plagiarism, self-plagiarism, and appropriate citation practices
• Image manipulation and data fabrication
• Declaration of conflicts of interest
• Ethics committee approval and informed consent
• Reporting responsibilities for animal and human studies
• Publication ethics violations and their consequences
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Week - 14 |
Peer Review, Manuscript Revision, and Student Presentations
Content:
• Overview of the peer-review process
• Roles of editors, reviewers, and authors
• Evaluating reviewer comments
• Preparing a response-to-reviewers letter
• Reconsidering a rejected manuscript
• Culture of scientific criticism
• Presentation of student project/manuscript drafts
• General course evaluation
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