| CODE | CPH3906 | ||||||||
| TITLE | Applied Statistics and Bioinformatics in Pharmacology | ||||||||
| UM LEVEL | 03 - Years 2, 3, 4 in Modular Undergraduate Course | ||||||||
| MQF LEVEL | 6 | ||||||||
| ECTS CREDITS | 4 | ||||||||
| DEPARTMENT | Clinical Pharmacology and Therapeutics | ||||||||
| DESCRIPTION | This study-unit will provide students with a comprehensive foundation in leveraging quantitative methods and computational tools to analyze complex biological data which is relevant to pharmacological applications. The programme integrates statistical modeling, data mining, analysis of molecular genetic and proteomic data, pathway analysis with relevance to drug mechanisms, prediction of functional relevance of pharmacogene variants, variant protein structure modeling, and the generation of diverse types of data visualization with interpretation. Through a blend of lectures and tutorial-based hands-on exercises, participants will gain practical training with the use of appropriate software tools. Emphasis will be placed on critical thinking and problem-solving skills. By the end of the unit, learners will be equipped to apply a selection of statistical and bioinformatics approaches to the rapidly advancing drug related molecular fields. Study-Unit Aims: - To equip students with the statistical principles and methods essential for analyzing pharmacological data. - To explain the techniques and major bioinformatics tools used in the analysis of genomic, proteomic, and pharmacogenomic data. - To offer hands-on experience with software tools commonly used in applied statistics and bioinformatics, ensuring students gain practical proficiency. - To demonstrate the integration of statistical and bioinformatics approaches in addressing complex problems in pharmacology - To appreciate how statistical and bioinformatics methods contribute to insights into drug mechanisms, efficacy, and safety. - To prepare students for further academic research or professional roles in fields requiring expertise in pharmacological data analysis. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Apply appropriate statistical analysis to pharmacology related data. - Use a selection of open access established bioinformatic tools, repositories, databases and knowledgebases in order to address real-world questions related to pharmacology research. - Identify reliable established resources of such tools and repositories - Organise data and generate appropriate visualizations for diverse types of bioinformatic analysis outputs. - Interpret, draw conclusions and appropriately report such analysis outputs. - Recognise the limitations of the analysis used, and propose potential alternative interpretations of output, where relevant. 2. Skills: By the end of the study-unit the student will be able to: - Demonstrate proficiency in using statistical and bioinformatics software. - Extract meaningful insights from complex datasets, - Apply problem-solving skills and quantitative reasoning to the analysis of datasets. - Translate complex data into clear, actionable reports and visualizations. - Synthesize information, and contribute to evidence-based conclusions. - Develop self-directed learning habits to keep pace with advancements in statistics, bioinformatics, and related fields. Main Text/s and any supplementary readings: Main Texts: - Salkind J. and Frey B.B. Statistics for People Who (Think They) Hate Statistics. 2019. 7th Ed. SAGE Publications, Inc (USA) - Pallant. SPSS Survival Manual: A Step by Step Guide to Data Analysis Using IBM SPSS. 2020. 7th ed. Ed. Open University Press. - There are no specific main texts required for the bioinformatics component. Students will be provided with respective guides to the software applications used, together with sample datasets which they can use as practice. Supplementary Readings: - Bioinformatics and Drug Discovery. Series Methods in Molecular Biology 1939, 3, 2019. Springer New York; Humana Press. |
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| ADDITIONAL NOTES | Pre-requisite Study-unit: CPH1910 Statistical Methods in Pharmacology | ||||||||
| STUDY-UNIT TYPE | Lecture | ||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Abigail Dalli David Paul Dimech Anthony Fenech (Co-ord.) Janet Mifsud Marita Vella |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2025/6. It may be subject to change in subsequent years. |
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