All Outputs (40)

Automatically Labeling Cyber Threat Intelligence reports using Natural Language Processing (2023)
Conference Proceeding

Attribution provides valuable intelligence in the face of Advanced Persistent Threat (APT) attacks. By accurately identifying the culprits and actors behind the attacks, we can gain more insights into their motivations, capabilities, and potential fu... Read More about Automatically Labeling Cyber Threat Intelligence reports using Natural Language Processing.

The Lanthipeptide Synthetase-like Protein CA_C0082 Is an Effector of Agr Quorum Sensing in Clostridium acetobutylicum (2023)
Journal Article

Lanthipeptide synthetases are present in all domains of life. They catalyze a crucial step during lanthipeptide biosynthesis by introducing thioether linkages during posttranslational peptide modification. Lanthipeptides have a wide range of function... Read More about The Lanthipeptide Synthetase-like Protein CA_C0082 Is an Effector of Agr Quorum Sensing in Clostridium acetobutylicum.

A genome-scale metabolic model of Cupriavidus necator H16 integrated with TraDIS and transcriptomic data reveals metabolic insights for biotechnological applications (2022)
Journal Article

Exploiting biological processes to recycle renewable carbon into high value platform chemicals provides a sustainable and greener alternative to current reliance on petrochemicals. In this regard Cupriavidus necator H16 represents a particularly prom... Read More about A genome-scale metabolic model of Cupriavidus necator H16 integrated with TraDIS and transcriptomic data reveals metabolic insights for biotechnological applications.

Software tools for green and sustainable chemistry (2022)
Journal Article

In this review, we consider green chemistry metrics, related software tools, and the opportunities and challenges for their use in research laboratories. We provide an overview of state-of-the-art software designed both to aid researchers in planning... Read More about Software tools for green and sustainable chemistry.

Engineering improved ethylene production: Leveraging systems Biology and adaptive laboratory evolution (2021)
Journal Article

Ethylene is a small hydrocarbon gas widely used in the chemical industry. Annual worldwide production currently exceeds 150 million tons, producing considerable amounts of CO2 contributing to climate change. The need for a sustainable alternative is... Read More about Engineering improved ethylene production: Leveraging systems Biology and adaptive laboratory evolution.

A Comprehensive Study of the Efficiency of Type-Reduction Algorithms (2020)
Journal Article

Improving the efficiency of type-reduction algorithms continues to attract research interest. Recently, there have been some new type-reduction approaches claiming that they are more efficient than the well-known algorithms such as the enhanced Karni... Read More about A Comprehensive Study of the Efficiency of Type-Reduction Algorithms.

Dual predation by bacteriophage and bdellovibrio bacteriovorus can eradicate escherichia coli prey in situations where single predation cannot (2020)
Journal Article

Copyright © 2020 Hobley et al. Bacteria are preyed upon by diverse microbial predators, including bacteriophage and predatory bacteria, such as Bdellovibrio bacteriovorus. While bacteriophage are used as antimicrobial therapies in Eastern Europe and... Read More about Dual predation by bacteriophage and bdellovibrio bacteriovorus can eradicate escherichia coli prey in situations where single predation cannot.

Modelling Emerging Pollutants in Wastewater Treatment: A Case Study using the Pharmaceutical 17??ethinylestradiol (2019)
Journal Article

Mathematical modelling can play a key role in understanding as well as quantifying uncertainties surrounding the presence and fate of emerging pollutants in wastewater treatment processes (WWTPs). This paper presents for the first time a simplified e... Read More about Modelling Emerging Pollutants in Wastewater Treatment: A Case Study using the Pharmaceutical 17??ethinylestradiol.

Microarray Feature Selection and Dynamic Selection of Classifiers for Early Detection of Insect Bite Hypersensitivity in Horses (2019)
Conference Proceeding

Microarrays can be employed to better characterise allergies, as interactions between antibodies and allergens in mammals can be monitored. Once the joint dynamics of these elements in both healthy and diseased animals are understood, a model to pred... Read More about Microarray Feature Selection and Dynamic Selection of Classifiers for Early Detection of Insect Bite Hypersensitivity in Horses.

Gsmodutils: a python based framework for test-driven genome scale metabolic model development (2019)
Journal Article

© 2019 The Author(s) 2019. Published by Oxford University Press. Motivation: Genome scale metabolic models (GSMMs) are increasingly important for systems biology and metabolic engineering research as they are capable of simulating complex steady-stat... Read More about Gsmodutils: a python based framework for test-driven genome scale metabolic model development.

Gsmodutils: A python based framework for test-driven genome scale metabolic model development (2018)
Other

Motivation Genome scale metabolic models (GSMMs) are increasingly important for systems biology and metabolic engineering research as they are capable of simulating complex steady-state behaviour. Constraints based models of this form can include tho... Read More about Gsmodutils: A python based framework for test-driven genome scale metabolic model development.

From clusters to queries: exploiting uncertainty in the modularity landscape of complex networks (2018)
Conference Proceeding

Uncovering latent community structure in complex networks is a field that has received an enormous amount of attention. Unfortunately, whilst potentially very powerful, unsupervised methods for uncovering labels based on topology alone has been shown... Read More about From clusters to queries: exploiting uncertainty in the modularity landscape of complex networks.

A comment on "A direct approach for determining the switch points in the Karnik-Mendel algorithm" (2018)
Journal Article

This letter is a supplement to the previous paper “A Direct Approach for Determining the Switch Points in the Karnik-Mendel Algorithm”. In the previous paper, the enhanced iterative algorithm with stop condition (EIASC) was shown to be the most ineff... Read More about A comment on "A direct approach for determining the switch points in the Karnik-Mendel algorithm".

Type-1 and interval type-2 ANFIS: a comparison (2017)
Conference Proceeding

In a previous paper, we proposed an extended ANFIS architecture and showed that interval type-2 ANFIS produced larger errors than type-1 ANFIS on the well-known IRIS classification problem. In this paper, more experiments on both synthetic and real-w... Read More about Type-1 and interval type-2 ANFIS: a comparison.

Measuring and modelling the response of Klebsiella pneumoniae KPC prey to Bdellovibrio bacteriovorus predation, in human serum and defined buffer (2017)
Journal Article

In worldwide conditions of increasingly antibiotic-resistant hospital infections, it is important to research alternative therapies. Bdellovibrio bacteriovorus bacteria naturally prey on Gram-negative pathogens, including antibiotic-resistant strains... Read More about Measuring and modelling the response of Klebsiella pneumoniae KPC prey to Bdellovibrio bacteriovorus predation, in human serum and defined buffer.

A Direct Approach for Determining the Switch Points in the Karnik–Mendel Algorithm (2017)
Journal Article

The Karnik-Mendel algorithm is used to compute the centroid of interval type-2 fuzzy sets, determining the switch points needed for the lower and upper bounds of the centroid, through an iterative process. It is commonly acknowledged that there is n... Read More about A Direct Approach for Determining the Switch Points in the Karnik–Mendel Algorithm.

A new accuracy measure based on bounded relative error for time series forecasting (2017)
Journal Article

Many accuracy measures have been proposed in the past for time series forecasting comparisons. However, many of these measures suffer from one or more issues such as poor resistance to outliers and scale dependence. In this paper, while summarising c... Read More about A new accuracy measure based on bounded relative error for time series forecasting.

An extended ANFIS architecture and its learning properties for type-1 and interval type-2 models (2016)
Conference Proceeding

In this paper, an extended ANFIS architecture is proposed. By incorporating an extra layer for the fuzzification process, the extended architecture is able to fit both type-1 and interval type-2 models. The learning properties of the proposed archite... Read More about An extended ANFIS architecture and its learning properties for type-1 and interval type-2 models.

Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis (2016)
Journal Article

Bambara groundnut (Vigna subterranea (L.) Verdc.) is an African legume and is a promising underutilized crop with good seed nutritional values. Low temperature stress in a number of African countries at night, such as Botswana, can effect the growth... Read More about Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis.

Infobiotics workbench: a P systems based tool for systems and synthetic biology (2013)
Book Chapter

This chapter gives an overview of an integrated software suite, the Infobiotics Workbench, which is based on a novel spatial discrete-stochastic P systems modelling framework. The Workbench incorporates three important features, simulation, model che... Read More about Infobiotics workbench: a P systems based tool for systems and synthetic biology.