Department of Chemistry course timetable

The course will outlay bioinformatic analysis of cell populations from single-cell RNA including visualisation, clustering and functional analysis of genes. This will be using the programming language R and packages such as Seurat. Participants are encouraged to bring their own laptop to follow along.

Lesson 1

• 4.00 - 4.45pm = Setting up
• 4.45 - 5.00pm = Break, questions
• 5.00 - 6.00pm = Introduction to scRNA-Seq

Lesson 2

• 1.00 - 1.45pm = QC, Normalising, Feature Selection
• 1.45 - 2.00pm = Break, questions
• 2.00 - 3.00pm = Scaling, Dimensionality reduction, Determining dimensionality of dataset

Lesson 3

• 1.00 - 1.45pm = Clustering, UMAP/t-SNE
• 1.45 - 2.00pm = Break, questions
• 2.00 - 3.00pm = Cluster biomarkers, Assigning cell type identity, Differential expression, Enrichment

Lesson 4

• 1.00 - 1.45pm = Work on dataset from Stanford/literature/own dataset
• 1.45 - 2.00pm = Break, questions
• 2.00 - 3.00pm = Work on dataset from Stanford/literature/own dataset

Chemistry plays a very crucial role in tackling 21st century global challenges. From climate change mitigation to discovering therapeutic strategies for human health and driving sustainable energy production and usage - we are faced with many challenges for which chemical sciences has been providing and will continue to provide many plausible solutions.

Much of the research involved in developing these initiatives requires a huge drive towards interdisciplinary research networks. As such, this course has been developed with some of our colleagues from across the Chemistry Department who are working on exciting and emerging areas with this multidisciplinary focus.

This course will introduce how chemistry can be used as a tool to solve these challenges. First session will include the introduction. Each lecture following this will focus on a different branch, area or concept of chemistry covering the fundamental chemistry and background of how it works, any advances to date and the applications towards tackling these global challenges.

The first session is compulsory, plus choose optional sessions you wish to attend when you make your booking.

• Session 1: Introduction

• Session 2: Organic Electronics

• Session 3: Electrochemistry (Batteries)

• Session 4: Third Generation Antibody Discovery Register on Zoom: https://tinyurl.com/ycq3zhg4

• Session 5: Chemical Reactions by Mill-Grinding (Mechanochemistry Synthetic Tool) Register on Zoom: https://tinyurl.com/yaf4o7hj

• Session 6: Electrochemistry: The Energy Storage Challenge Register on Zoom: https://tinyurl.com/yak5oe6h

• Session 7: Transition Metal Catalysis for Pharmaceutical and Agrochemical Applications Register on Zoom: https://tinyurl.com/yavuxfgq

• Session 8: Air Pollution and Climate Change Register on Zoom: https://tinyurl.com/yc62s4ko

In this session, Dr. Mukund S. Chorghade will discuss the pivotal role played by Process Chemistry / Route Selection in the progress of a drug from conception to commercialization. The medicinal chemistry routes for synthesis are usually low yielding and are fraught with capricious reactions, cryogenic temperatures, tedious chromatography and problems in scale-up to multi-kilo and multi-ton levels. Considerable research efforts have to be expended in developing novel, cost efficacious and scalable processes and seamlessly transferring these technologies to manufacturing operations. These principles will be exemplified by process development case studies on a variety of pharmaceutical moieties such as anti-epileptic and an anti-asthma drugs. We were able to also discover a large number of New Chemical Entities by our new “Process Chemistry Driven Medicinal Chemistry”

We will exemplify advances in proprietary in vitro green chemistry-based technology, mimicking in vivo metabolism of several chemical entities used in pharmaceuticals, cosmetics, and agrochemicals. Our catalysts enable prediction of metabolism patterns with soft-spot analysis Metabolites are implicated in adverse drug reactions and are the subject of intense scrutiny in drug R&D. Present-day processes involving animal studies are expensive, labor-intensive and chemically inconclusive. Our catalysts (azamacrocycles) are sterically protected and electronically activated, providing speed, stability and scalability. We predict structures of metabolites, prepare them on a large scale by oxidation, and elucidate chemical structures. Comprehensive safety evaluation enables researchers to conduct more complete in vitro metabolism studies, confirm structure and generate quantitative measures of toxicity.

A ‘recommended’ optional course for Chemistry graduates that introduces all the relevant online databases available to you in the university: citation databases such as Web of Science, Scopus, and PubMed, which index all the scientific literature that is published, as well as chemistry and related subject-specific databases. You will be guided on how to search citation databases effectively and the session includes a hands-on element where you can practice - please bring your own laptop.

The session will be most suitable for those who are new to searching citation databases or would like a refresher.

Please note that this session will not cover searching the databases Reaxys and SciFinder. These are covered by IS5.

• Please bring your own laptop so you can participate in the practical element of the session

The course will outlay bioinformatic analysis of cell populations from single-cell RNA including visualisation, clustering and functional analysis of genes. This will be using the programming language R and packages such as Seurat. Participants are encouraged to bring their own laptop to follow along.

Lesson 1

• 4.00 - 4.45pm = Setting up
• 4.45 - 5.00pm = Break, questions
• 5.00 - 6.00pm = Introduction to scRNA-Seq

Lesson 2

• 1.00 - 1.45pm = QC, Normalising, Feature Selection
• 1.45 - 2.00pm = Break, questions
• 2.00 - 3.00pm = Scaling, Dimensionality reduction, Determining dimensionality of dataset

Lesson 3

• 1.00 - 1.45pm = Clustering, UMAP/t-SNE
• 1.45 - 2.00pm = Break, questions
• 2.00 - 3.00pm = Cluster biomarkers, Assigning cell type identity, Differential expression, Enrichment

Lesson 4

• 1.00 - 1.45pm = Work on dataset from Stanford/literature/own dataset
• 1.45 - 2.00pm = Break, questions
• 2.00 - 3.00pm = Work on dataset from Stanford/literature/own dataset

Chemistry plays a very crucial role in tackling 21st century global challenges. From climate change mitigation to discovering therapeutic strategies for human health and driving sustainable energy production and usage - we are faced with many challenges for which chemical sciences has been providing and will continue to provide many plausible solutions.

Much of the research involved in developing these initiatives requires a huge drive towards interdisciplinary research networks. As such, this course has been developed with some of our colleagues from across the Chemistry Department who are working on exciting and emerging areas with this multidisciplinary focus.

This course will introduce how chemistry can be used as a tool to solve these challenges. First session will include the introduction. Each lecture following this will focus on a different branch, area or concept of chemistry covering the fundamental chemistry and background of how it works, any advances to date and the applications towards tackling these global challenges.

The first session is compulsory, plus choose optional sessions you wish to attend when you make your booking.

• Session 1: Introduction

• Session 2: Organic Electronics

• Session 3: Electrochemistry (Batteries)

• Session 4: Third Generation Antibody Discovery Register on Zoom: https://tinyurl.com/ycq3zhg4

• Session 5: Chemical Reactions by Mill-Grinding (Mechanochemistry Synthetic Tool) Register on Zoom: https://tinyurl.com/yaf4o7hj

• Session 6: Electrochemistry: The Energy Storage Challenge Register on Zoom: https://tinyurl.com/yak5oe6h

• Session 7: Transition Metal Catalysis for Pharmaceutical and Agrochemical Applications Register on Zoom: https://tinyurl.com/yavuxfgq

• Session 8: Air Pollution and Climate Change Register on Zoom: https://tinyurl.com/yc62s4ko

The first half of this session will cover an overview of Raytracing versus 3D Modelling, an introduction to the free Raytracing programme Povray, running Povray (command line options). Making and manipulating simple shapes, camera tricks (depth of field, angle of view) and using other software to generate Povray input (e.g. Jmol)

The second half of the session is an introduction to 3D modelling and animation using the open source programme Blender. This will cover the installation and customisation of the Blender interface for use with chemical models, how to import chemical structures from Jmol and the protein data base (PDB), the basics of 3D modelling, and an introduction to Key-frame animation.

No previous experience with either 3D modelling or animation is required.

The course will outlay bioinformatic analysis of cell populations from single-cell RNA including visualisation, clustering and functional analysis of genes. This will be using the programming language R and packages such as Seurat. Participants are encouraged to bring their own laptop to follow along.

Lesson 1

• 4.00 - 4.45pm = Setting up
• 4.45 - 5.00pm = Break, questions
• 5.00 - 6.00pm = Introduction to scRNA-Seq

Lesson 2

• 1.00 - 1.45pm = QC, Normalising, Feature Selection
• 1.45 - 2.00pm = Break, questions
• 2.00 - 3.00pm = Scaling, Dimensionality reduction, Determining dimensionality of dataset

Lesson 3

• 1.00 - 1.45pm = Clustering, UMAP/t-SNE
• 1.45 - 2.00pm = Break, questions
• 2.00 - 3.00pm = Cluster biomarkers, Assigning cell type identity, Differential expression, Enrichment

Lesson 4

• 1.00 - 1.45pm = Work on dataset from Stanford/literature/own dataset
• 1.45 - 2.00pm = Break, questions
• 2.00 - 3.00pm = Work on dataset from Stanford/literature/own dataset

A thorough awareness of issues relating to research ethics and research integrity are essential to producing excellent research. This session will provide an introduction to the ethical responsibilities of researchers at the University, publication ethics and research integrity. It will be interactive, using case studies to better understand key ethical issues and challenges in all areas. There are three sessions running, you need attend only one.

This compulsory session introduces Research Data Management (RDM) to Chemistry PhD students. It is highly interactive and utilises practical activities throughout.

Key topics covered are:

• Research Data Management (RDM) - what it is and what problems can occur with managing and sharing your data.
• Data backup and file sharing - possible consequences of not backing up your data, strategies for backing up your data and sharing your data safely.
• Data organisation - how to organise your files and folders, what is best practice.
• Data sharing - obstacles to sharing your data, benefits and importance of sharing your data, the funder policy landscape, resources available in the University to help you share your data.
• Data management planning - creating a roadmap for how not to get lost in your data!

The course will outlay bioinformatic analysis of cell populations from single-cell RNA including visualisation, clustering and functional analysis of genes. This will be using the programming language R and packages such as Seurat. Participants are encouraged to bring their own laptop to follow along.

Lesson 1

• 4.00 - 4.45pm = Setting up
• 4.45 - 5.00pm = Break, questions
• 5.00 - 6.00pm = Introduction to scRNA-Seq

Lesson 2

• 1.00 - 1.45pm = QC, Normalising, Feature Selection
• 1.45 - 2.00pm = Break, questions
• 2.00 - 3.00pm = Scaling, Dimensionality reduction, Determining dimensionality of dataset

Lesson 3

• 1.00 - 1.45pm = Clustering, UMAP/t-SNE
• 1.45 - 2.00pm = Break, questions
• 2.00 - 3.00pm = Cluster biomarkers, Assigning cell type identity, Differential expression, Enrichment

Lesson 4

• 1.00 - 1.45pm = Work on dataset from Stanford/literature/own dataset
• 1.45 - 2.00pm = Break, questions
• 2.00 - 3.00pm = Work on dataset from Stanford/literature/own dataset

Unconscious Bias refers to the biases we hold that are not in our conscious control. Research shows that these biases can adversely affect key decisions in the workplace. The session will enable you to work towards reducing the effects of unconscious bias for yourself and within your organisation. Using examples that you will be able to relate to, we help you to explore the link between implicit bias and the impact on the organisation. The overall aim of the session is to provide participants with an understanding of the nature of Unconscious Bias and how it impacts on individual and group attitudes, behaviours and decision-making processes.

The main aim of giving a presentation to the public or a science venue is to present information in a way that the audience will remember at a later time. There are several ways in which we can improve this type of impact with an audience. This interactive lecture explores some of those mechanisms.

This session will require 4-5 volunteers to provide a 10 min talk which the session will show how to improve. Presenters in the following week's Peer to Peer presentations will be given priority booking for this event.

Submission of the PhD thesis can seem to be a daunting experience, from constructing it to submitting and then being examined, with one of those examiners coming from an external institution. In this session, Marie Dixon (Degree Committee Office, School of Physical Sciences), Rachel MacDonald and Deborah Longbottom will talk through all aspects of procedure regarding thesis submission and answer any questions students wish to pose. Students who were recently examined, as well as members of academic staff who carry out PhD vivas will also be there to talk about the reality of the process from all perspectives

Submission of the first year report can seem to be a daunting experience, from constructing it to submitting and then being assessed by academic staff. In this session, Marie Dixon (Degree Committee Office, School of Physical Sciences), Rachel MacDonald and Deborah Longbottom will talk through all aspects of procedure and answer any questions students wish to pose. Students who went through the first year exam in 2016, as well as members of academic staff who carry out first year vivas will also be there to talk about the reality of the process from all perspectives.

The current situation is a difficult one, with labs closed, and the need for home-working (where possible). It is particularly challenging for those thinking about their post-Ph.D careers, where communication with potential employers is cut-off and job offers are being put back or cancelled.

This session is aimed at Ph.D students, especially those that are ‘in limbo’, unable to work in the Lab, isolated at home or whose job offers may have been delayed or cancelled.

Kevin Parker will narrate his own work experience, firstly at an Oil Company and then freelancing for 25 years, both in terms of what he did and the key personal skills needed to carry out each job.

The session will finish with an overview of the skills various important employers are looking for in graduate recruits, along with advice on how to survive job-hunting and/or home working.