Effects of boundary conditions on irreversible dynamics

We present a simple one-dimensional Ising-type spin system on which we define a completely asymmetric Markovian single spin-flip dynamics. We study the system at a very low, yet non-zero, temperature and we show that for empty boundary conditions the Gibbs measure is stationary for such dynamics, while introducing in a single site a $+$ condition the stationary measure changes drastically, with macroscopical effects. We achieve this result defining an absolutely convergent series expansion of the stationary measure around the zero temperature system. Interesting combinatorial identities are involved in the proofs

Phase transitions for the cavity approach to the clique problem on random graphs

We give a rigorous proof of two phase transitions for a disordered system designed to find large cliques inside Erdos random graphs. Such a system is associated with a conservative probabilistic cellular automaton inspired by the cavity method originally introduced in spin glass theory.Comment: 36 pages, 4 figure

Tunneling and Metastability of continuous time Markov chains

We propose a new definition of metastability of Markov processes on countable state spaces. We obtain sufficient conditions for a sequence of processes to be metastable. In the reversible case these conditions are expressed in terms of the capacity and of the stationary measure of the metastable states

Metastability of non-reversible mean-field Potts model with three spins

We examine a non-reversible, mean-field Potts model with three spins on a set with $N\uparrow\infty$ points. Without an external field, there are three critical temperatures and five different metastable regimes. The analysis can be extended by a perturbative argument to the case of small external fields. We illustrate the case of large external fields with some phenomena which are not present in the absence of external field.Comment: 34 pages, 12 figure

Ideal gas approximation for a two-dimensional rarefied gas under Kawasaki dynamics

Article / Letter to editorMathematisch Instituu

Bigger, Faster, Better? Rhetorics and Practices of Large-Scale Research in Contemporary Bioscience

publication-status: Publishedtypes: ArticleEditorial for Special Issu

Predicting Spontaneous Preterm Birth Using the Immunome

Throughout pregnancy, the maternal peripheral circulation contains valuable information reflecting pregnancy progression, detectable as tightly regulated immune dynamics. Local immune processes at the maternal-fetal interface and other reproductive and non-reproductive tissues are likely to be the pacemakers for this peripheral immune "clock." This cellular immune status of pregnancy can be leveraged for the early risk assessment and prediction of spontaneous preterm birth (sPTB). Systems immunology approaches to sPTB subtypes and cross-tissue (local and peripheral) interactions, as well as integration of multiple biological data modalities promise to improve our understanding of preterm birth pathobiology and identify potential clinically actionable biomarkers.</p

Discovery of sparse, reliable omic biomarkers with Stabl

Adoption of high-content omic technologies in clinical studies, coupled with computational methods, has yielded an abundance of candidate biomarkers. However, translating such findings into bona fide clinical biomarkers remains challenging. To facilitate this process, we introduce Stabl, a general machine learning method that identifies a sparse, reliable set of biomarkers by integrating noise injection and a data-driven signal-to-noise threshold into multivariable predictive modeling. Evaluation of Stabl on synthetic datasets and five independent clinical studies demonstrates improved biomarker sparsity and reliability compared to commonly used sparsity-promoting regularization methods while maintaining predictive performance; it distills datasets containing 1,400-35,000 features down to 4-34 candidate biomarkers. Stabl extends to multi-omic integration tasks, enabling biological interpretation of complex predictive models, as it hones in on a shortlist of proteomic, metabolomic and cytometric events predicting labor onset, microbial biomarkers of pre-term birth and a pre-operative immune signature of post-surgical infections. Stabl is available at https://github.com/gregbellan/Stabl

Local mutations:On the tentative beginnings of molecular oncology in Britain 1980–2000

Popular and scientific accounts of the molecularisation of cancer typically attribute it to advances in laboratory science, particularly molecular geneticists. However, historical research has indicated that clinical expertise input was often vital for advancing such work. The present paper reinforces that view. Looking in detail at British research into the molecular genetics of familial cancers during the 1980s and 1990s, it shows that that research, too, depended on crucial input from family cancer clinics. Moreover, the development of clinical services for familial cancers was in turn shaped by the demands of contributing to molecular genetic research. The paper concludes that accounts of the molecularisation of cancer that suppose a one-way transfer of knowledge and practice from laboratory to clinic misrepresent the complex interactions that were involved in molecularising familial cancers, and that were informed by the particular local and national circumstances in which they took shape