Research Insights

Research Insights section focuses on the cutting-edge and breakthrough research that is happening all over the world. Laboratories across the globe are working hard to develop drugs and therapies for various diseases and research insights directly from them add tremendous value.

Mechanobiological model for simulation of injured cartilage degradation via pro-inflammatory cytokines and mechanical stimulus

Posttraumatic osteoarthritis PTOA is associated with cartilage degradation ultimately leading to disability and decrease of quality of life Two key mechanisms have been suggested to occur in PTOA tissue inflammation

Stochastic ordering of complexoform protein assembly by genetic circuits

Topdown proteomics has enabled the elucidation of heterogeneous protein complexes with different cofactors posttranslational modifications and protein membership This heterogeneity is believed to play a previously unknown role in cellular processes

Statistical analysis of 3D localisation microscopy images for quantification of membrane protein distributions in a platelet clot model

We present the software platform CALM that allows for a comparative analysis of D localisation microscopy data representing protein distributions in two biological samples The indepth statistical analysis reveals differences between samples at the nanoscopic level

Early transmission of sensitive strain slows down emergence of drug resistance in Plasmodium vivax

The spread of drug resistance of Plasmodium falciparum and Plasmodium vivax parasites is a challenge towards malaria elimination P falciparum has shown an early and severe drug resistance in comparison to P vivax in various countries

A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks

Metabolism underpins the pathogenic strategy of the causative agent of TB Mycobacterium tuberculosis Mtb and therefore metabolic pathways have recently reemerged as attractive drug targets A powerful approach to study Mtb metabolism as a whole

Benchmarking Predictions of MHC Class I Restricted T Cell Epitopes in a Comprehensively Studied Model System

T cell epitope candidates are commonly identified using computational prediction tools in order to enable applications such as vaccine design cancer neoantigen identification development of diagnostics and removal of unwanted immune responses against protein therapeutics

In Silico Analysis of Hypoxia Activated Prodrugs in Combination with Anti Angiogenic Therapy through Nanocell Delivery

Tumour hypoxia is a wellstudied phenomenon with implications in cancer progression treatment resistance and patient survival While a clear adverse prognosticator hypoxia is also a theoretically ideal target for guided drug delivery

Balance between Asymmetry and Abundance in Multi-Domain DNA-Binding Proteins may Regulate the Kinetics of their Binding to DNA

DNA sequences are often recognized by multidomain proteins that may have higher affinity and specificity than singledomain proteins However the higher affinity to DNA might be coupled with slower recognition kinetics In this study we address this balance between stability and kinetics for multidomain CysHis CH type zincfinger ZF proteins

Predicting Host Taxonomic information from Viral Genomes: A comparison of Feature Representations

The rise in metagenomics has led to an exponential growth in virus discovery However the majority of these new virus sequences have no assigned host Current machine learning approaches to predicting virus host interactions have a tendency

Network Mechanisms and Dysfunction within an Integrated Computational Model of Progression through Mitosis in the Human Cell Cycle

The cellular proteinprotein interaction network that governs cellular proliferation cell cycle is highly complex Here we have developed a novel computational model of human mitotic cell cycle integrating diverse cellular mechanisms