A Heuristic Ontological Model of Protein Complexes A Case Study Based on the E3 Ubiquitin Ligase Protein Complexes of Arabidopsis thaliana

Ontology (with a capital O) is the philosophical study of the nature of existence that was derived to define the relationships of entities that can be said to exist in nature. The concept of an ontology was later adopted by the biological sciences to formally represent knowledge within a biological domain in order to standardize the annotation of biological data, and further, enable more efficient and easier data collection, sharing, and reuse across biological and model organism databases. The Protein Ontology (PRO) is a specific biological ontology developed to represent the relationships between proteins and protein complexes. This thesis presents a revised PRO framework, modelled around Arabidopsis thaliana and associated SCF ubiquitin ligase complexes, with the aim to more adequately represent what is known about the process and dynamics of protein complex formation in order to better serve the broader scientific community

A comparison of the molecular organization of genomic regions associated with resistance to common bacterial blight in two Phaseolus vulgaris genotypes

Resistance to common bacterial blight, caused by Xanthomonas axonopodis pv. phaseoli, in Phaseolus vulgaris is conditioned by several loci on different chromosomes. Previous studies with OAC-Rex, a CBB-resistant, white bean variety of Mesoamerican origin, identified two resistance loci associated with the molecular markers Pv-CTT001 and SU91, on chromosome 4 and 8, respectively. Resistance to CBB is assumed to be derived from an interspecific cross with Phaseolus acutifolius in the pedigree of OAC-Rex. Our current whole genome sequencing effort with OAC-Rex provided the opportunity to compare its genome in the regions associated with CBB resistance with the v1.0 release of the P. vulgaris line G19833, which is a large seeded bean of Andean origin, and (assumed to be) CBB susceptible. In addition, the genomic regions containing SAP6, a marker associated with P. vulgaris-derived CBB-resistance on chromosome 10, were compared. These analyses indicated that gene content was highly conserved between G19833 and OAC-Rex across the regions examined ( \u3e 80%). However, fifty-nine genes unique to OAC Rex were identified, with resistance gene homologues making up the largest category (10 genes identified). Two unique genes in OAC-Rex located within the SU91 resistance QTL have homology to P. acutifolius ESTs and may be potential sources of CBB resistance. As the genomic sequence assembly of OAC-Rex is completed, we expect that further comparisons between it and the G19833 genome will lead to a greater understanding of CBB resistance in bean

The IASLC Early Lung Imaging Confederation (ELIC) Open-Source Deep Learning and Quantitative Measurement Initiative.

BackgroundWith global adoption of CT lung cancer screening, there is increasing interest to use artificial intelligence (AI) deep learning methods to improve the clinical management process. To enable AI research using an open source, cloud-based, globally distributed, screening CT imaging dataset and computational environment that are compliant with the most stringent international privacy regulations that also protects the intellectual properties of researchers, the International Association of the Study of Lung Cancer (IASLC) sponsored development of the Early Lung Imaging Confederation (ELIC) resource in 2018. The objective of this report is to describe the updated capabilities of ELIC and illustrate how this resource can be utilized for clinically relevant AI research.MethodsIn this second Phase of the initiative, metadata and screening CT scans from two time points were collected from 100 screening participants in seven countries. An automated deep learning AI lung segmentation algorithm, automated quantitative emphysema metrics, and a quantitative lung nodule volume measurement algorithm were run on these scans.ResultsA total of 1,394 CTs were collected from 697 participants. The LAV950 quantitative emphysema metric was found to be potentially useful in distinguishing lung cancer from benign cases using a combined slice thickness ≥ 2.5 mm. Lung nodule volume change measurements had better sensitivity and specificity for classifying malignant from benign lung nodules when applied to solid lung nodules from high quality CT scans.ConclusionThese initial experiments demonstrated that ELIC can support deep learning AI and quantitative imaging analyses on diverse and globally distributed cloud-based datasets

Tracking Cancer Evolution Reveals Constrained Routes to Metastases: TRACERx Renal.

Clear-cell renal cell carcinoma (ccRCC) exhibits a broad range of metastatic phenotypes that have not been systematically studied to date. Here, we analyzed 575 primary and 335 metastatic biopsies across 100 patients with metastatic ccRCC, including two cases sampledat post-mortem. Metastatic competence was afforded by chromosome complexity, and we identify 9p loss as a highly selected event driving metastasis and ccRCC-related mortality (p = 0.0014). Distinct patterns of metastatic dissemination were observed, including rapid progression to multiple tissue sites seeded by primary tumors of monoclonal structure. By contrast, we observed attenuated progression in cases characterized by high primary tumor heterogeneity, with metastatic competence acquired gradually and initial progression to solitary metastasis. Finally, we observed early divergence of primitive ancestral clones and protracted latency of up to two decades as a feature of pancreatic metastases

Tracking Cancer Evolution Reveals Constrained Routes to Metastases: TRACERx Renal.

Clear-cell renal cell carcinoma (ccRCC) exhibits a broad range of metastatic phenotypes that have not been systematically studied to date. Here, we analyzed 575 primary and 335 metastatic biopsies across 100 patients with metastatic ccRCC, including two cases sampledat post-mortem. Metastatic competence was afforded by chromosome complexity, and we identify 9p loss as a highly selected event driving metastasis and ccRCC-related mortality (p = 0.0014). Distinct patterns of metastatic dissemination were observed, including rapid progression to multiple tissue sites seeded by primary tumors of monoclonal structure. By contrast, we observed attenuated progression in cases characterized by high primary tumor heterogeneity, with metastatic competence acquired gradually and initial progression to solitary metastasis. Finally, we observed early divergence of primitive ancestral clones and protracted latency of up to two decades as a feature of pancreatic metastases