Folding the human proteome using BioNeMo: A fused dataset of structural models for machine learning purposes.

Human proteins are crucial players in both health and disease. Understanding their molecular landscape is a central topic in biological research. Here, we present an extensive dataset of predicted protein structures for 42,042 distinct human proteins, including splicing variants, derived from the UniProt reference proteome UP000005640.

A graphical model approach visualizes regulatory relationships between genome-wide transcription factor binding profiles.

Integrated analysis of multiple genome-wide transcription factor (TF)-binding profiles will be vital to advance our understanding of the global impact of TF binding. However, existing methods for measuring similarity in large numbers of chromatin immunoprecipitation assays with sequencing (ChIP-seq), such as correlation, mutual information or enrichment analysis, are limited in their ability to display functionally relevant TF relationships. In this study, we propose the use of graphical models to determine conditional independence between TFs and showed that network visualization provides a promising alternative to distinguish 'direct' versus 'indirect' TF interactions.

DNMT3A Loss Drives Enhancer Hypomethylation in FLT3-ITD-Associated Leukemias.

DNMT3A, the gene encoding the de novo DNA methyltransferase 3A, is among the most frequently mutated genes in hematologic malignancies. However, the mechanisms through which DNMT3A normally suppresses malignancy development are unknown. Here, we show that DNMT3A loss synergizes with the FLT3 internal tandem duplication in a dose-influenced fashion to generate rapid lethal lymphoid or myeloid leukemias similar to their human counterparts.

Data Science Solution to Event Prediction in Outsourced Clinical Trial Models.

Late phase clinical trials are regularly outsourced to a Contract Research Organisation (CRO) while the risk and accountability remain within the sponsor company. Many statistical tasks are delivered by the CRO and later revalidated by the sponsor. Here, we report a technological approach to standardised event prediction.

Constrained transcription factor spacing is prevalent and important for transcriptional control of mouse blood cells.

Combinatorial transcription factor (TF) binding is essential for cell-type-specific gene regulation. However, much remains to be learned about the mechanisms of TF interactions, including to what extent constrained spacing and orientation of interacting TFs are critical for regulatory element activity. To examine the relative prevalence of the 'enhanceosome' versus the 'TF collective' model of combinatorial TF binding, a comprehensive analysis of TF binding site sequences in large scale datasets is necessary.

CODEX: a next-generation sequencing experiment database for the haematopoietic and embryonic stem cell communities.

CODEX (http://codex.stemcells.cam.

TRES predicts transcription control in embryonic stem cells.

Summary: Unraveling transcriptional circuits controlling embryonic stem cell maintenance and fate has great potential for improving our understanding of normal development as well as disease. To facilitate this, we have developed a novel web tool called 'TRES' that predicts the likely upstream regulators for a given gene list. This is achieved by integrating transcription factor (TF) binding events from 187 ChIP-sequencing and ChIP-on-chip datasets in murine and human embryonic stem (ES) cells with over 1000 mammalian TF sequence motifs.

Disease risk factors identified through shared genetic architecture and electronic medical records.

Genome-wide association studies have identified genetic variants for thousands of diseases and traits. We evaluated the relationships between specific risk factors (for example, blood cholesterol level) and diseases on the basis of their shared genetic architecture in a comprehensive human disease-single-nucleotide polymorphism association database (VARIMED), analyzing the findings from 8962 published association studies. Similarity between traits and diseases was statistically evaluated on the basis of their association with shared gene variants.

Systematic identification of DNA variants associated with ultraviolet radiation using a novel Geographic-Wide Association Study (GeoWAS).

Background: Long-term environmental variables are widely understood to play important roles in DNA variation. Previously, clinical studies examining the impacts of these variables on the human genome were localized to a single country, and used preselected DNA variants. Furthermore, clinical studies or surveys are either not available or difficult to carry out for developing countries.

Systematic identification of risk factors for Alzheimer's disease through shared genetic architecture and electronic medical records.

Alzheimer's disease (AD) is one of the leading causes of death for older people in US with rapidly increasing incidence. AD irreversibly and progressively damages the brain, but there are treatments in clinical trials to potentially slow the development of AD. We hypothesize that the presence of clinical traits, sharing common genetic variants with AD, could be used as a non-invasive means to predict AD or trigger for administration of preventative therapeutics.

Quantifying multi-ethnic representation in genetic studies of high mortality diseases.

Most GWASs were performed using study populations with Caucasian ethnicity or ancestry, and findings from one ethnic subpopulation might not always translate to another. We curated 4,573 genetic studies on 763 human diseases and identified 3,461 disease-susceptible SNPs with genome-wide significance; only 10% of these had been validated in at least two different ethnic populations. SNPs for autoimmune diseases demonstrated the lowest percentage of cross-ethnicity validation.

Integrative approach to pain genetics identifies pain sensitivity loci across diseases.

Identifying human genes relevant for the processing of pain requires difficult-to-conduct and expensive large-scale clinical trials. Here, we examine a novel integrative paradigm for data-driven discovery of pain gene candidates, taking advantage of the vast amount of existing disease-related clinical literature and gene expression microarray data stored in large international repositories. First, thousands of diseases were ranked according to a disease-specific pain index (DSPI), derived from Medical Subject Heading (MESH) annotations in MEDLINE.

Type 2 diabetes risk alleles demonstrate extreme directional differentiation among human populations, compared to other diseases.

Many disease-susceptible SNPs exhibit significant disparity in ancestral and derived allele frequencies across worldwide populations. While previous studies have examined population differentiation of alleles at specific SNPs, global ethnic patterns of ensembles of disease risk alleles across human diseases are unexamined. To examine these patterns, we manually curated ethnic disease association data from 5,065 papers on human genetic studies representing 1,495 diseases, recording the precise risk alleles and their measured population frequencies and estimated effect sizes.

Sex differences in reported pain across 11,000 patients captured in electronic medical records.

Unlabelled: Clinically recorded pain scores are abundant in patient health records but are rarely used in research. The use of this information could help improve clinical outcomes. For example, a recent report by the Institute of Medicine stated that ineffective use of clinical information contributes to undertreatment of patient subpopulations--especially women.

Comparison of automated and human assignment of MeSH terms on publicly-available molecular datasets.

Publicly available molecular datasets can be used for independent verification or investigative repurposing, but depends on the presence, consistency and quality of descriptive annotations. Annotation and indexing of molecular datasets using well-defined controlled vocabularies or ontologies enables accurate and systematic data discovery, yet the majority of molecular datasets available through public data repositories lack such annotations. A number of automated annotation methods have been developed; however few systematic evaluations of the quality of annotations supplied by application of these methods have been performed using annotations from standing public data repositories.

Neural induction intermediates exhibit distinct roles of Fgf signaling.

Formation of the neural plate is an intricate process in early mammalian embryonic development mediated by cells of the inner cell mass and involving a series of steps, including development of the epiblast. Here, we report on the creation of an embryonic stem (ES) cell-based system to isolate and identify neural induction intermediates with characteristics of epiblast cells and neural plate. We demonstrate that neural commitment requires prior differentiation of ES cells into epiblast cells that are indistinguishable from those derived from natural embryos.

Activated Notch1 target genes during embryonic cell differentiation depend on the cellular context and include lineage determinants and inhibitors.

Background: Notch receptor signaling controls developmental cell fates in a cell-context dependent manner. Although Notch signaling directly regulates transcription via the RBP-J/CSL DNA binding protein, little is known about the target genes that are directly activated by Notch in the respective tissues.

Methodology/principal Findings: To analyze how Notch signaling mediates its context dependent function(s), we utilized a Tamoxifen-inducible system to activate Notch1 in murine embryonic stem cells at different stages of mesodermal differentiation and performed global transcriptional analyses.

Gold nanoparticles of diameter 1.4 nm trigger necrosis by oxidative stress and mitochondrial damage.

Gold nanoparticles (AuNPs) are generally considered nontoxic, similar to bulk gold, which is inert and biocompatible. AuNPs of diameter 1.4 nm capped with triphenylphosphine monosulfonate (TPPMS), Au1.

Induction of pluripotency in adult unipotent germline stem cells.

Mouse and human stem cells with features similar to those of embryonic stem cells have been derived from testicular cells. Although pluripotent stem cells have been obtained from defined germline stem cells (GSCs) of mouse neonatal testis, only multipotent stem cells have been obtained so far from defined cells of mouse adult testis. In this study we describe a robust and reproducible protocol for obtaining germline-derived pluripotent stem (gPS) cells from adult unipotent GSCs.

GAR22: a novel target gene of thyroid hormone receptor causes growth inhibition in human erythroid cells.

Objective: Thyroid hormone receptors (TRs) are ligand-dependent transcription factors with a major impact on erythroid cell development. Here we investigated TR activity on red cell gene expression and identified TR target genes. The impact of the TR target gene GAR22 (growth arrest-specific 2 [GAS2]-related gene on chromosome 22) on red cell differentiation was determined.

Oct4-induced pluripotency in adult neural stem cells.

The four transcription factors Oct4, Sox2, Klf4, and c-Myc can induce pluripotency in mouse and human fibroblasts. We previously described direct reprogramming of adult mouse neural stem cells (NSCs) by Oct4 and either Klf4 or c-Myc. NSCs endogenously express Sox2, c-Myc, and Klf4 as well as several intermediate reprogramming markers.

The transcription factor repertoire of Flt3+ hematopoietic stem cells.

Hematopoietic stem cells maintain the development of all mature blood cells throughout life due to their sustained self-renewal capacity and multilineage differentiation potential. During development into specific cell lineages, the options of stem cells and multipotent progenitor cells become increasingly restricted concomitant with a successive decline in self-renewal potential. Here we describe an Flt3+CD11b+ multipotent progenitor that can be amplified in vitro with a specific combination of cytokines to yield homogeneous populations in high cell numbers.

Pluripotent stem cells induced from adult neural stem cells by reprogramming with two factors.

Reprogramming of somatic cells is a valuable tool to understand the mechanisms of regaining pluripotency and further opens up the possibility of generating patient-specific pluripotent stem cells. Reprogramming of mouse and human somatic cells into pluripotent stem cells, designated as induced pluripotent stem (iPS) cells, has been possible with the expression of the transcription factor quartet Oct4 (also known as Pou5f1), Sox2, c-Myc and Klf4 (refs 1-11). Considering that ectopic expression of c-Myc causes tumorigenicity in offspring and that retroviruses themselves can cause insertional mutagenesis, the generation of iPS cells with a minimal number of factors may hasten the clinical application of this approach.