Knowledge graphs can support many biomedical applications. These graphs represent biomedical concepts and relationships in the form of nodes and edges. In this review, we discuss how these graphs are constructed and applied with a particular focus on how machine learning approaches are changing these processes. Biomedical knowledge graphs have often been constructed by integrating databases that were

Advancements in the field of next generation sequencing lead to the generation of ever-more data, with the challenge often being how to combine and reconcile results from different OMICs studies such as genome, epigenome and transcriptome. Here we provide an overview of the standard processing pipelines for ChIP-seq and RNA-seq as well as common downstream analyses. We describe popular multi-omics

The MinION sequencer by Oxford Nanopore Technologies turns DNA and RNA sequencing into a routine task in biology laboratories or in field research. For downstream analysis it is required to have a sufficien[t amount of target reads. Especially prokaryotic or bacteriophagic sequencing samples can contain a significant amount of off-target sequences in the processed sample, stemming from human DNA/RNA

The rise of material science and nanotechnology created a demand for a next generation of materials and procedures that can transcend the shaping of simple geometrical nano-objects. As a legacy of the technological progress made in the Human Genome Project, DNA was identified as a possible candidate. The low production costs of custom-made DNA molecules and the possibilities concerning the structural

Single-cell transcriptomics offers a powerful way to reveal the heterogeneity of individual cells. To date, many information theoretical approaches have been proposed to assess diversity and similarity, and characterize the latent heterogeneity in transcriptome data. Diversity implies gene expression variations and can facilitate the identification of signature genes; while, similarity unravels co-expression

Multispecific antibodies can be generated in different formats. More than two decades of R&D in the field of bispecific antibody engineering revealed that the design and choice of format can have a profound impact on the antibody functionality. This holds in particular true for entities that elicit (inter-)cellular processes such as receptor activation, receptor internalization, receptor clustering

[This corrects the article DOI: 10.1016/j.csbj.2018.09.003.].

Genetic interactions (GIs) are fundamental to our understanding of biological processes in the cell. While GIs have been systematically mapped in yeast, there is scarce information about them in humans. Recently, we have suggested a state-of-the-art hierarchical method that leverages gene ontology information for predicting GIs in yeast. Here, we adapt this method and apply it for the first time to

Puromycin is a naturally occurring aminonucleoside antibiotic that inhibits protein synthesis by ribosome-catalyzed incorporation into the C-terminus of elongating nascent chains, blocking further extension and resulting in premature termination of translation. It is most commonly known as a selection marker for cell lines genetically engineered to express a resistance transgene, but its additional

Parkinson's disease (PD), Alzheimer's disease (AD) and Amyotrophic lateral sclerosis (ALS) are neurodegenerative diseases hallmarked by the formation of toxic protein aggregates. However, targeting these aggregates therapeutically have thus far shown no success. The treatment of AD has remained particularly problematic since no new drugs have been approved in the last 15 years. Therefore, novel therapeutic

Clinical exome sequencing (CES) has become a routine diagnostic tool in several pediatric subspecialties, with a reported average diagnostic yield of ~25% in this patient poulation. The utility of CES in the United Arab Emirates (UAE) has not been previously investigated, most likely due to the lack of the appropriate tertiary pediatric centers and diagnostic genomic facilities in this country. Here

The methodologies and software packages for mapping quantitative trait loci (QTLs) in bi-parental segregation populations are well established. However, it is still difficult to detect small-effect and linked QTLs. To address this issue, we proposed a genome-wide composite interval mapping (GCIM) in bi-parental segregation populations. To popularize this method, we developed an R package. This program

Bone morphogenetic proteins (BMP) are members of the transforming growth factor β superfamily (TGF-β). BMPs are involved in tumourigenesis and disease progression of certain malignancies. To date, the role played by BMPs in gastric cancer (GC) remains largely unknown. In the present study, we systematically analysed the expression and clinical significance of BMP and BMP receptors (BMPR) in TCGA gastric

Microbial ecosystems of the built environments have become key mediators of health as people worldwide tend to spend large amount of time indoors. Underexposure to microbes at an early age is linked to increased risks of allergic and autoimmune diseases. Transportation systems are of particular interest, as they are globally the largest space for interactions between city-dwellers. Here we performed