Causality, Information and Biological Computation: An algorithmic software approach to life, disease and the immune system

Biology has taken strong steps towards becoming a computer science aiming at reprogramming nature after the realisation that nature herself has reprogrammed organisms by harnessing the power of natural selection and the digital prescriptive nature of replicating DNA. Here we further unpack ideas related to computability, algorithmic information theory and software engineering, in the context of the extent to which biology can be (re)programmed, and with how we may go about doing so in a more systematic way with all the tools and concepts offered by theoretical computer science in a translation exercise from computing to molecular biology and back. These concepts provide a means to a hierarchical organization thereby blurring previously clear-cut lines between concepts like matter and life, or between tumour types that are otherwise taken as different and may not have however a different cause. This does not diminish the properties of life or make its components and functions less interesting. On the contrary, this approach makes for a more encompassing and integrated view of nature, one that subsumes observer and observed within the same system, and can generate new perspectives and tools with which to view complex diseases like cancer, approaching them afresh from a software-engineering viewpoint that casts evolution in the role of programmer, cells as computing machines, DNA and genes as instructions and computer programs, viruses as hacking devices, the immune system as a software debugging tool, and diseases as an information-theoretic battlefield where all these forces deploy. We show how information theory and algorithmic programming may explain fundamental mechanisms of life and death.Comment: 30 pages, 8 figures. Invited chapter contribution to Information and Causality: From Matter to Life. Sara I. Walker, Paul C.W. Davies and George Ellis (eds.), Cambridge University Pres

Systemic lupus erythematosus in African-American women: immune cognitive modules, autoimmune disease, and pathogenic social hierarchy

Examining elevated rates of systemic lupus erythematosus in African-American women from the perspective of the emerging theory of immune cognition suggests the disease constitutes an internalized physiological image of external patterns of psychosocial stress, a 'pathogenic social hierarchy' involving the synergism of racism and gender discrimination. The disorder represents the punctuated resetting of 'normal' immune self-image to a self-attacking 'excited' state, a process formally analogous to models of punctuated equilibrium in evolutionary theory. We speculate that this punctuated onset takes place in the context of an immunological 'cognitive module' similar to what has been proposed by evolutionary psychologists for the human mind. We discuss the broader implications of a high rate of this disorder within a marginalized population, finding it to be a leading indicator for phenomena likely to entrain powerful subgroups into a larger pattern of embedding patholog

Ontology-based knowledge representation of experiment metadata in biological data mining

According to the PubMed resource from the U.S. National Library of Medicine, over 750,000 scientific articles have been published in the ~5000 biomedical journals worldwide in the year 2007 alone. The vast majority of these publications include results from hypothesis-driven experimentation in overlapping biomedical research domains. Unfortunately, the sheer volume of information being generated by the biomedical research enterprise has made it virtually impossible for investigators to stay aware of the latest findings in their domain of interest, let alone to be able to assimilate and mine data from related investigations for purposes of meta-analysis. While computers have the potential for assisting investigators in the extraction, management and analysis of these data, information contained in the traditional journal publication is still largely unstructured, free-text descriptions of study design, experimental application and results interpretation, making it difficult for computers to gain access to the content of what is being conveyed without significant manual intervention. In order to circumvent these roadblocks and make the most of the output from the biomedical research enterprise, a variety of related standards in knowledge representation are being developed, proposed and adopted in the biomedical community. In this chapter, we will explore the current status of efforts to develop minimum information standards for the representation of a biomedical experiment, ontologies composed of shared vocabularies assembled into subsumption hierarchical structures, and extensible relational data models that link the information components together in a machine-readable and human-useable framework for data mining purposes

Inverse comorbidity: the power of paradox in the advancement of science

Research on comorbidity and multimorbidity is finally receiving the attention it deserves, particularly considering the magnitude and impact they have on health and the delivery of healthcare [1,2]. Numerous studies have demonstrated that individuals with Down’s syndrome, Parkinson’s disease, schizophrenia, diabetes, anorexia nervosa, Alzheimer’s disease, allergy related diseases, multiple sclerosis or Huntington’s disease (among other health problems) are protected against many forms of cancer, including solid tumors, smoking-related tumors and prostate cancer. This apparent anti-cancer effect, which we have termed inverse cancer comorbidity, has been observed in many serious CNS and immune disorders, and is the subject of active research [3–5].Journal of Comorbidity 2013;3(1):1–3

Frontiers in Pigment Cell and Melanoma Research

We identify emerging frontiers in clinical and basic research of melanocyte biology and its associated biomedical disciplines. We describe challenges and opportunities in clinical and basic research of normal and diseased melanocytes that impact current approaches to research in melanoma and the dermatological sciences. We focus on four themes: (1) clinical melanoma research, (2) basic melanoma research, (3) clinical dermatology, and (4) basic pigment cell research, with the goal of outlining current highlights, challenges, and frontiers associated with pigmentation and melanocyte biology. Significantly, this document encapsulates important advances in melanocyte and melanoma research including emerging frontiers in melanoma immunotherapy, medical and surgical oncology, dermatology, vitiligo, albinism, genomics and systems biology, epidemiology, pigment biophysics and chemistry, and evolution

The Oral Tolerance as a Complex Network Phenomenon

Date of Acceptance: 23/05/2015 Funding: MSB acknowledges the Engineering and Physical Sciences Research Council (EPSRC) - UK grant EP/I032606/1. PJM and MD received regular scholarships from the Brazilian the following agency: Higher Education Personnel Training Coordination (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) CAPES http://www.fisica.uepg.br:7080/ppgfisica​/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Cancer biomarkers, and novel techniques for detection

Technologies for early detection of tumors is critical for better therapy outcome and overall change in cancer survival. These assays must be capable of detecting tumors at early stages in order to prevent metastasis of the tumor and help reduce mortality. Biological molecules can serve as markers that can indicate the presence of cancerous cells. Current biomarkers approved by the FDA include CA 125, which is a tumor associated antigen (TAA). However, the sensitivities of these TAAs is not high enough to detect at early stages of disease. Recent technologies have found that antibodies that recognize these TAAs, also known as autoantibodies, provide more sensitive means to screen for tumors. This review aims to present recent literature data relative to the field of cancer diagnosis and treatment. However, one should note that this article covers only fraction of the broad science behind this subject