Long Non-Coding RNAs in Sjögren's Disease.

Sjögren's disease (SjD) is a heterogeneous autoimmune disease characterized by severe dryness of mucosal surfaces, particularly the mouth and eyes; fatigue; and chronic pain. Chronic inflammation of the salivary and lacrimal glands, auto-antibody formation, and extra-glandular manifestations occur in subsets of patients with SjD. An aberrant expression of long, non-coding RNAs (lncRNAs) has been described in many autoimmune diseases, including SjD. Here, we review the current literature on lncRNAs in SjD and their role in regulating X chromosome inactivation, immune modulatory functions, and their potential as biomarkers

"BNClassifier: Classifying Boolean Models by Dynamic Properties" Paper Artifact

<p>This is an artifact for the TACAS24 tool paper <i>"BNClassifier: Classifying Boolean Models by Dynamic Properties"</i>. The repository contains prepared tool binaries, the tool's source code, all benchmark models, and instructions on reproducing the results presented in the paper. For further instructions, follow the README.md file attached as part of the repository.</p&gt

"BNClassifier: Classifying Boolean Models by Dynamic Properties" Paper Artifact

<p>This is an artifact for the TACAS24 tool paper <i>"BNClassifier: Classifying Boolean Models by Dynamic Properties"</i>. The repository contains prepared tool binaries, the tool's source code, all benchmark models, and instructions on reproducing the results presented in the paper. For further instructions, follow the README.md file attached as part of the repository.</p&gt

Boolean network sketches: A unifying framework for logical model inference

Motivation: The problem of model inference is of fundamental importance to systems biology. Logical models (e.g. Boolean networks; BNs) represent a computationally attractive approach capable of handling large biological networks. The models are typically inferred from experimental data. However, even with a substantial amount of experimental data supported by some prior knowledge, existing inference methods often focus on a small sample of admissible candidate models only. Results: We propose Boolean network sketches as a new formal instrument for the inference of Boolean networks. A sketch integrates (typically partial) knowledge about the network’s topology and the update logic (obtained through, e.g. a biological knowledge base or a literature search), as well as further assumptions about the properties of the network’s transitions (e.g. the form of its attractor landscape), and additional restrictions on the model dynamics given by the measured experimental data. Our new BNs inference algorithm starts with an ‘initial’ sketch, which is extended by adding restrictions representing experimental data to a ‘data-informed’ sketch and subsequently computes all BNs consistent with the data-informed sketch. Our algorithm is based on a symbolic representation and coloured model-checking. Our approach is unique in its ability to cover a broad spectrum of knowledge and efficiently produce a compact representation of all inferred BNs. We evaluate the method on a non-trivial collection of real-world and simulated data

Linking aberrant glycosylation of plasma glycoproteins with progression of myelodysplastic syndromes: a study based on plasmonic biosensor and lectin array

Abstract Aberrant glycosylation of glycoproteins has been linked with various pathologies. Therefore, understanding the relationship between aberrant glycosylation patterns and the onset and progression of the disease is an important research goal that may provide insights into cancer diagnosis and new therapy development. In this study, we use a surface plasmon resonance imaging biosensor and a lectin array to investigate aberrant glycosylation patterns associated with oncohematological disease—myelodysplastic syndromes (MDS). In particular, we detected the interaction between the lectins and glycoproteins present in the blood plasma of patients (three MDS subgroups with different risks of progression to acute myeloid leukemia (AML) and AML patients) and healthy controls. The interaction with lectins from Aleuria aurantia (AAL) and Erythrina cristagalli was more pronounced for plasma samples of the MDS and AML patients, and there was a significant difference between the sensor response to the interaction of AAL with blood plasma from low and medium-risk MDS patients and healthy controls. Our data also suggest that progression from MDS to AML is accompanied by sialylation of glycoproteins and increased levels of truncated O-glycans and that the number of lectins that allow discriminating different stages of disease increases as the disease progresses