John Warwicker

John Warwicker, graphic designer, typographer, photographer and writer discusses his work

A unified framework for bivariate clustering and regression problems via mixed-integer linear programming

Clustering and regression are two of the most important problems in data analysis and machine learning. Recently, mixed-integer linear programs (MILPs) have been presented in the literature to solve these problems. By modelling the problems as MILPs, they are able to be solved very quickly by commercial solvers. In particular, MILPs for bivariate clusterwise linear regression (CLR) and (continuous) piecewise linear regression (PWLR) have recently appeared. These MILP models make use of binary variables and logical implications modelled through big-$\mathcal{M}$ constraints. In this paper, we present these models in the context of a unifying MILP framework for bivariate clustering and regression problems. We then present two new formulations within this framework, the first for ordered CLR, and the second for clusterwise piecewise linear regression (CPWLR). The CPWLR problem concerns simultaneously clustering discrete data, while modelling each cluster with a continuous PWL function. Extending upon the framework, we discuss how outlier detection can be implemented within the models, and how specific decomposition methods can be used to find speedups in the runtime. Experimental results show when each model is the most effective

Mechanisms for stabilisation and the maintenance of solubility in proteins from thermophiles

BACKGROUND: The database of protein structures contains representatives from organisms with a range of growth temperatures. Various properties have been studied in a search for the molecular basis of protein adaptation to higher growth temperature. Charged groups have emerged as key distinguishing factors for proteins from thermophiles and mesophiles. RESULTS: A dataset of 291 thermophile-derived protein structures is compared with mesophile proteins. Calculations of electrostatic interactions support the importance of charges, but indicate that increases in charge contribution to folded state stabilisation do not generally correlate with the numbers of charged groups. Relative propensities of charged groups vary, such as the substitution of glutamic for aspartic acid sidechains. Calculations suggest an energetic basis, with less dehydration for longer sidechains. Most other properties studied show weak or insignificant separation of proteins from moderate thermophiles or hyperthermophiles and mesophiles, including an estimate of the difference in sidechain rotameric entropy upon protein folding. An exception is increased burial of alanine and proline residues and decreased burial of phenylalanine, methionine, tyrosine and tryptophan in hyperthermophile proteins compared to those from mesophiles. CONCLUSION: Since an increase in the number of charged groups for hyperthermophile proteins is separable from charged group contribution to folded state stability, we hypothesise that charged group propensity is important in the context of protein solubility and the prevention of aggregation. Accordingly we find some separation between mesophile and hyperthermophile proteins when looking at the largest surface patch that does not contain a charged sidechain. With regard to our observation that aromatic sidechains are less buried in hyperthermophile proteins, further analysis indicates that the placement of some of these groups may facilitate the reduction of folding fluctuations in proteins of the higher growth temperature organisms

Compuchtational prediction of expression and solubility of recombinant biopharmaceuticals

Protein based therapeutics have emerged as a successful class of pharmaceutical. However, it is well known that much of the current therapeutic protein discovery and development processes is based around existing molecular frameworks and that novel formats offer significant challenges for expression. Efficient production of protein is required to meet the growing demands and increasing expectation of the patients and healthcare providers. Major obstacles during biopharmaceutical production are linked to the efficiency of the protein expression system and the biophysical properties of proteinbased products that can lead to aggregation and subsequent problems for purification, quality and effectiveness. Computational tools have been developed to aid prediction of protein solubility and aggregation propensity to support enhanced certainty of optimal generation of product with desirable properties. In this study, we have used an in-house computational tool for prediction of soluble protein expression (developed around protein structure and surface electrostatic properties of human erythropoietin, HuEPO) was developed in E. coli and has been validated experimentally with several bacteriallyexpressed model protein variants. The application of the computational approach has been extended to mammalian expression platforms. A significant inverse correlation was observed between positive surface patches and the expressability of HuEPO in transient mammalian cells (HEK and CHO cell lines). Mechanistically the differential expression operates at a level post-transcriptionally, associated with ribosome-secretory complex engagement, protein stability or secretory processes. The results demonstrate the potential of application of a predictive computational algorithm as a design tool in rational protein engineering to improve expression of novel protein formats in mammalian systems as well as E.coli. In summary, optimization of molecular patches on the surface of proteins may be a viable strategy to enhance protein soluble expression and therefore a potential solution for development of novel proteins that might otherwise fit into the category of “difficult-toexpress” proteins

Objective researcher or emotional being?

This is an accepted manuscript of an article published by the Faculty of Health & Welling, University of Wolverhampton in Journal of Health and Social Care Improvement on 31/01/2020, available online: https://www.wlv.ac.uk/media/departments/faculty-of-health-education-and-wellbeing/pdf/may-2020-v3-journal.pdf The accepted version of the publication may differ from the final published version.I am a second year PhD student exploring dyadic coping among spousal carers of partners living with dementia. In laying the foundations for my research, I have spent eighteen months attending and supporting two dementia cafés’. During this time, I have focused on better understanding dementia and its implications for spousal carers. I have also focussed on building a rapport with carers of those living with dementia so that they feel comfortable with my presence and to develop their trust in me. This is an important part of researcher integration which is all too often overlooked and can strengthen qualitative research findings (Collins & Cooper, 2014)

Polyunsaturated fatty acids inhibit k_v1.4 by interacting with positively charged extracellular pore residues

Polyunsaturated fatty acids (PUFAs) modulate voltage-gated K(+) channel inactivation by an unknown site and mechanism. The effects of ω-6 and ω-3 PUFAs were investigated on the heterologously expressed K(v)1.4 channel. PUFAs inhibited wild-type K(v)1.4 during repetitive pulsing as a result of slowing of recovery from inactivation. In a mutant K(v)1.4 channel lacking N-type inactivation, PUFAs reversibly enhanced C-type inactivation (K(d), 15–43 μM). C-type inactivation was affected by extracellular H(+) and K(+) as well as PUFAs and there was an interaction among the three: the effect of PUFAs was reversed during acidosis and abolished on raising K(+). Replacement of two positively charged residues in the extracellular pore (H508 and K532) abolished the effects of the PUFAs (and extracellular H(+) and K(+)) on C-type inactivation but had no effect on the lipoelectric modulation of voltage sensor activation, suggesting two separable interaction sites/mechanisms of action of PUFAs. Charge calculations suggest that the acidic head group of the PUFAs raises the pK(a) of H508 and this reduces the K(+) occupancy of the selectivity filter, stabilizing the C-type inactivated state