Nicos Angelopoulos

Cardiff University | CU · School of Medicine

Background: Glioblastoma is the most prevalent and severe type of malignant brain tumor in adults. Although the genetic make-up initiating glioblastoma is increasingly better understood, a better understanding in the mechanisms that drive its evolution, heterogeneity and therapy resistance may reveal new directions for therapy development. To get b...

Bayesian networks (BNs) are disciplined, explainable Artificial Intelligence models that can describe structured joint probability spaces. In the context of understanding complex relations between a number of variables in biological settings, they can be constructed from observed data and can provide a guiding, graphical tool in exploring such rela...

Mutational signatures have emerged as powerful biomarkers in cancer patients, with prognostic and therapeutic implications. Wider clinical utility requires access to reproducible algorithms, which allow characterization of mutational signatures in a given tumor sample. Here, we show how mutational signature fitting can be applied to hematological c...

The landscape of structural variants (SVs) in multiple myeloma remains poorly understood. Here, we performed comprehensive analysis of SVs in a large cohort of 752 multiple myeloma patients by low coverage long-insert whole genome sequencing. We identified 68 SV hotspots involving 17 new candidate driver genes, including the therapeutic targets BCM...

The evolution and progression of multiple myeloma and its precursors over time is poorly understood. Here, we investigate the landscape and timing of mutational processes shaping multiple myeloma evolution in a large cohort of 89 whole genomes and 973 exomes. We identify eight processes, including a mutational signature caused by exposure to melpha...

Antibody combinations targeting cell surface receptors are a new modality of cancer therapy. The trafficking and signalling mechanisms regulated by such therapeutics are not fully understood but could underlie differential tumour responses. We explored EGFR trafficking upon treatment with the antibody combination Sym004 which has shown promise clin...

The landscape of structural variants (SVs) in multiple myeloma remains poorly understood. Here, we performed comprehensive classification and analysis of SVs in multiple myeloma, interrogating a large cohort of 762 patients with whole genome and RNA sequencing. We identified 100 SV hotspots involving 31 new candidate driver genes, including drug ta...

Purpose: Precision medicine trials in glioblastoma (GBM) are often conducted at tumor recurrence. However, second surgeries for recurrent GBM are not routinely performed, and therefore, molecular data for trial inclusion are predominantly derived from the primary sample. This study aims to establish whether molecular targets change during tumor pr...

INTRODUCTION: Cancer pathogenesis is usually characterized by a long evolutionary process where genomic driver events accumulate over time, conferring advantage to distinct subclones, allowing their expansion and progression. METHODS: To investigate the multiple myeloma (MM) evolutionary history, we characterized the mutational processes' landscape...

Delivering effective data analytics is of crucial importance to the interpretation of the multitude of biological datasets currently generated by an ever increasing number of high throughput techniques. Logic programming has much to offer in this area. Here, we detail advances that highlight two of the strengths of logical formalisms in developing...

Delivering effective data analytics is of crucial importance to the interpretation of the multitude of biological datasets currently generated by an ever increasing number of high throughput techniques. Logic programming has much to offer in this area. Here, we detail advances that highlight two of the strengths of logical formalisms in developing...

The multiple myeloma (MM) genome is heterogeneous and evolves through preclinical and post-diagnosis phases. Here we report a catalog and hierarchy of driver lesions using sequences from 67 MM genomes serially collected from 30 patients together with public exome datasets. Bayesian clustering defines at least 7 genomic subgroups with distinct sets...

Multiple Myeloma (MM) initiation and progression is driven by recurrent cytogenetic events, i.e. multiple trisomies or translocations within the immunoglobulin locus. Gene mutations have been extensively studied, and they are generally involved in late phases of disease development. On the contrary, very little is known about non-recurrent structur...

Background Myeloproliferative neoplasms, such as polycythemia vera, essential thrombocythemia, and myelofibrosis, are chronic hematologic cancers with varied progression rates. The genomic characterization of patients with myeloproliferative neoplasms offers the potential for personalized diagnosis, risk stratification, and treatment. Methods We s...

Clear cell renal cell carcinoma (ccRCC) is characterized by near-universal loss of the short arm of chromosome 3, deleting several tumor suppressor genes. We analyzed whole genomes from 95 biopsies across 33 patients with clear cell renal cell carcinoma. We find hotspots of point mutations in the 5′ UTR of TERT, targeting a MYC-MAX-MAD1 repressor a...

Clear cell renal cell carcinoma (ccRCC) is characterized by near-universal loss of the short arm of chromosome 3, deleting several tumor suppressor genes. We analyzed whole genomes from 95 biopsies across 33 patients with clear cell renal cell carcinoma. We find hotspots of point mutations in the 5' UTR of TERT, targeting a MYC-MAX-MAD1 repressor a...

Leukemia accepted article preview online, 06 December 2017. doi:10.1038/leu.2017.345.

It has been argued before that Prolog is a strong candidate for research and code development in bioinformatics and computational biology. This position has been based on both the intrinsic strengths of Prolog and recent advances in its technologies. Here we strengthen the case for the deployment and penetration of Prolog into bioinformatics, by in...

We present a formalism for combining logic programming and its flavour of nondeterminism with probabilistic reasoning. In particular, we focus on representing prior knowledge for Bayesian inference. Distributional logic programming (Dlp), is considered in the context of a class of generative probabilistic languages. A characterisation based on prob...

Oncogenic signalling and metabolic reprograming are hallmarks of tumour progression, yet little is known about the regulatory elements that coordinate their interface. Aberrant choline and phospholipid metabolism are strongly correlated to malignant progression in NSCLC and provide the essential components required by both hallmarks and yet mechani...

We present recent developments on the syntax of Real, a library for interfacing two Prolog systems to the statistical language R. We focus on the changes in Prolog syntax within SWI-Prolog that accommodate greater syntactic integration, enhanced user experience and improved features for web-services. We recount the full syntax and functionality of...

Tyrosine kinases (TKs) play an essential role in regulating various cellular activities and dysregulation of TK signaling contributes to oncogenesis. However, less than half of the TKs have been thoroughly studied. Through a combined use of RNAi and stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative proteomics, a gl...

LMTK3 is an oncogenic receptor tyrosine kinase (RTK) implicated in various types of cancer, including breast, lung, gastric, and colorectal cancer. It is local- izedindifferentcellularcompartments,butitsnuclear functionhasnotbeeninvestigatedsofar.Wemapped LMTK3 binding across the genome using ChIP-seq and found that LMTK3 binding events are corre-...

Tyrosine kinases (TKs) are central regulators in cellular activities and perturbations of TK signaling contribute to oncogenesis. However, less than half of the TKs have been thoroughly studied and a global functional analysis of their proteomic portrait is lacking. Here we conducted a combined approach of RNAi and stable isotope labeling with amin...

Kinase suppressor of Ras 1 (KSR1) has been implicated in tumorigenesis in multiple cancers, including skin, pancreatic and lung carcinomas. However, our recent study revealed a role of KSR1 as a tumour suppressor in breast cancer, the expression of which is potentially correlated with chemotherapy response. Here, we aimed to further elucidate the K...

The composition and structure of the pregnancy vaginal microbiome may influence susceptibility to adverse pregnancy outcomes. Studies on the pregnant vaginal microbiome have largely been limited to Northern American populations. Using MiSeq sequencing of 16S rRNA gene amplicons, we characterised the vaginal microbiota of a mixed British cohort of w...

Cell migration is crucial in development, tissue repair and immunity and frequently aberrant in pathological processes including tumor metastasis. Focal adhesions (FAs) are integrin-based adhesion complexes that form the link between the cytoskeleton and the extracellular matrix and are thought to orchestrate cell migration. Understanding the regul...

We present recent developments on the syntax of Real, a library for interfacing two Prolog systems to the statistical language R. We focus on the changes in Prolog syntax within SWI-Prolog that accommodate greater syntactic integration, enhanced user experience and improved features for web-services. We recount the full syntax and functionality of...

It has been argued before that Prolog is a strong candidate for research and code development in bioinformatics and computational biology. This position has been based on both the intrinsic strengths of Prolog and recent advances in its technologies. Here we strengthen the case for the deployment and penetration of Prolog into bioinformatics, by in...

Acquired or de novo resistance to trastuzumab remains a barrier to patient survival and mechanisms underlying this still remain unclear. Using stable isotope labelling by amino acids in cell culture (SILAC)-based quantitative proteomics to compare proteome profiles between trastuzumab sensitive/resistant cells, we identified autophagy related prote...

This volume contains the papers presented at CICLOPS'12: 12th International Colloquium on Implementation of Constraint and LOgic Programming Systems held on Tueseday September 4th, 2012 in Budapest. The program included 1 invited talk, 9 technical presentations and a panel discussion on Prolog open standards (open.pl). Each programme paper was revi...

We present r..eal, a library that integrates the R statistical environment with Prolog. Due to R's functional programming affinity the interface introduced has a minimalistic feel. Programs utilising the library syntax are elegant and suc-cinct with intuitive semantics and clear integration. In effect, the library enhances logic programming with th...

We present a succinct yet powerful interface library to the SQLite database system. The single file, server-less approach of SQLite along with the natural integration of relational data within Prolog, render the library a useful addition to the existing database libraries in modern open-source engines. We detail the architecture and predicates of t...

We present a general framework for defining priors on model structure and sampling from the posterior using the Metropolis-Hastings algorithm. The key idea is that structure priors are defined via a probability tree and that the proposal mechanism for the Metropolis-Hastings algorithm operates by traversing this tree, thereby defining a cheaply com...

In high throughput screening a large number of molecules are tested against a single target protein to determine binding affinity of each molecule to the target. The objective of such tests within the pharmaceutical industry is to identify potential drug-like lead molecules. Current technology allows for thousands of molecules to be tested inexpens...

Todays applications are typically programmed in multiple languages, using SQL to access databases, JavaScript to make the (web-based) user interface interactive, etc. Prolog can cooperate to this orchestra using two views: as a logic server component or as 'glue'. In this article we concentrate on the 'glue' view, which implies that we must be able...

We present a succinct yet powerful interface library to the SQLite database system. The single file, serverless approach of SQLite along with the natural integration of relational data within Prolog, render the library a useful addition to the existing database libraries in modern open-source engines. We detail the architecture and predicates of th...

We present the first study of protein regulation by ligands in Caenorhabditis elegans. The ligands were peptidyl-prolyl isomerase inhibitors of cyclophilins. Up-regulation is observed for several heat shock proteins and one ligand in particular caused a greater than 2-fold enhancement of cyclophilin CYN-5. Additionally, several metabolic enzymes di...

This paper presents a generic web-based database interface implemented in Prolog. We discuss the advantages of the implementation platform and demonstrate the system's applicability in providing access to integrated biochemical data. Our system exploits two libraries of SWI-Prolog to create a schema-transparent interface within a relational setting...

In high throughput screening a large number of molecules are tested against a single target protein to determine binding affinity of each molecule to the target. The objective of such tests within the pharmaceutical industry is to identify potential drug-like lead molecules. Current technology allows for thousands of molecules to be tested inexpens...

High-throughput screening (HTS) is now a standard approach used in the pharmaceutical industry to identify potential drug-like lead molecules. The analysis linking biological data with molecular properties is a major goal in both academic and pharmaceutical research. This paper presents a Bayesian analysis of high-dimensional descriptor data using...

This paper presents and evaluates an approach to Bayesian model averaging where the models are Bayesian nets (BNs). A comprehensive study of the literature on structural priors for BNs is conducted. A number of prior distributions are defined using stochastic logic programs and the MCMC Metropolis-Hastings algorithm is used to (approximately) sampl...

A general method for defining informative priors on statistical models is presented and applied specifically to the space of classification and regression trees. A Bayesian approach to learning such models from data is taken, with the Metropolis- Hastings algorithm being used to approximately sample from the posterior. By only using proposal distri...

This paper concerns the experimental assess- ment of tempering as a technique for im- proving Bayesian inference for C&RT mod- els. Full Bayesian inference requires the computation of a posterior over all possible trees. Since exact computation is not pos- sible Markov chain Monte Carlo (MCMC) methods are used to produce an approxi- mation. C&RT po...

In this paper we extend a methodology for Bayesian learning via MCMC, with the ability to grow arbitrarily long branches in C&RT models. We are able to do so by exploiting independence in the model construction process. The ability to grow branches rather than single nodes has been noted as desirable in the literature. The most singular feature of...

We present a language for integrating probabilistic reasoning and logic programming. The key idea is to use constraints based techniques such as the constraints store and finite domain variables. First we show how these techniques can be used to integrate a number of probabilistic inference algorithms with logic programming. We then proceed to deta...

We show how the amalgamation of Logic Programming with probabilistic reasoning enhances its capabilities for intelligent reasoning. Unlike current approaches we use concepts from Constraint Logic Programming in order to achieve this. In particular, we use the constraint store for storing probabilistic information and inference, and finite domains a...

We argue that the clp(X) framework is a suitable vehicle for extending logic programming (LP) with probabilistic reasoning. This paper presents such a generic framework, clp(pdf(Y)), and proposes two promising instances. The first provides a seamless integration of Bayesian Networks, while the second defines distributions over variables and employs...

We present a Markov chain Mode Carlo algorithm that operates on generic model structures that are represented by terms found in the computed answers produced by stochastic logic programs. The objective of this paper is threefold (a) to show that SLD-trees are an elegant means for describing prior distributions over model structures (b) to sketch an...

In this paper we present a simple source code configuration tool. ExLibris operates on libraries and can be used to extract from local libraries all code relevant to a particular project. Our approach is not designed to address problems arising in code production lines, but rather, to support the needs of individual or small teams of researchers wh...

We propose a new way of extending Logic Programming (LP) for reasoning with uncertainty. Probabilistic finite domains (Pfd) capitalise on ideas introduced by Constraint LP, on how to extend the reasoning capabilities of the LP engine. Unlike other approaches to the field, Pfd syntax can be intuitively related to the axioms defining Probability and...

Developments in our ability to integrate and analyze data held in existing heterogeneous data resources can lead to an increase in our understanding of biological function at all levels. However, supporting ad hoc queries across multiple data resources and correlating data retrieved from these is still difficult. To address this, we are building a...

Abstract We present a Markov chain Mode Carlo algorithm that operates on generic model structures that are represented by terms found in the computed answers produced by stochastic logic programs The objective of this paper is threefold (a) to show that SLD - trees are an elegant means for describing prior distributions over model structures (b) to...

The newly established standards of CORBA and XML make it much easier to interoperate between different database software running on different platforms. We are using these in a mediator-based architecture that supports integrated access to biological databases. We discuss, in turn, design issues that arise from using each of the standards. In CORBA...

Developments in our ability to integrate and analyse the data held in existing heterogeneous data resources can lead to an increase in our understanding of biological function at all levels. However, supporting ad-hoc queries across multiple data resources and correlating the data retrieved from these is still difficult. To address this, we are bui...

We propose a declarative-based implementation of randomised algorithms, which exploits the Constraint Logic Programming (CLP) paradigm. For the high-level formalisation of probabilistic programs expressing such algorithms we actually refer to a generalisation of CLP, namely the Probabilistic Concurrent Constraint Programming (PCCP) language, previo...

this paper, we propose a declarative-based implementation of randomised algorithms, which exploits the Concurrent Constraint Programming (CCP) paradigm for the formalisation of such algorithms. The main advantage in doing so is that we can rely on a sound and mathematically rigorous semantical framework, instead of on intuition, for tasks related t...

We propose a declarative-based implementation of randomised algorithms, which exploits the Constraint Logic Programming (CLP) paradigm. For the high-level formalisation of probabilistic programs expressing such algorithms we actually refer to a generalisation of CLP, namely the Probabilistic Concurrent Constraint Programming (PCCP) language, previo...

We propose a declarative-based implementation of randomised algorithms, which exploits the Constraint Logic Programming (CLP) paradigm. For the high-level formalisation of probabilistic programs expressing such algorithms we actually refer to a generalisation of CLP, namely the Probabilistic Concurrent Constraint Programming (PCCP) language, previo...

This report contains four sections (Domain, Questions, Objectives and Methodology) proceeding through them from the abstract issues to more concrete ones. In these an attempt is made to place the general framework within which the current work is perceived. 2 Domain

This work is an attempt to bring forward and amalgamate a number of different technologies. Our motivation originates in extending the classical Logic Programming paradigm for effective reasoning over disjunctive information. In doing so we take aboard notions from the area of constraint satisfaction. We generalise these notions by allowing user-de...

A general method for defining informative priors on statis-tical models is presented and applied specifically to the space of classifi-cation and regression trees. Our aim is towards a Bayesian approach to learning such models from data, with the Metropolis-Hastings algorithm used to sample from the posterior. We present some preliminary results wh...

Thesis (Ph. D.)--City University, 2001.