DeGeCI 1.1: a web platform for gene annotation of mitochondrial genomes.

Summary: DeGeCI is a command line tool that generates fully automated gene predictions from mitochondrial nucleotide sequences by using a reference database of annotated mitogenomes which is represented as a de Bruijn graph. The input genome is mapped to this graph, creating a subgraph, which is then post-processed by a clustering routine. Version 1.

Towards Human-Centered Explainable AI: A Survey of User Studies for Model Explanations.

Explainable AI (XAI) is widely viewed as a sine qua non for ever-expanding AI research. A better understanding of the needs of XAI users, as well as human-centered evaluations of explainable models are both a necessity and a challenge. In this paper, we explore how human-computer interaction (HCI) and AI researchers conduct user studies in XAI applications based on a systematic literature review.

Fully automated annotation of mitochondrial genomes using a cluster-based approach with de Bruijn graphs.

A wide range of scientific fields, such as forensics, anthropology, medicine, and molecular evolution, benefits from the analysis of mitogenomic data. With the development of new sequencing technologies, the amount of mitochondrial sequence data to be analyzed has increased exponentially over the last few years. The accurate annotation of mitochondrial DNA is a prerequisite for any mitogenomic comparative analysis.

Detecting gene breakpoints in noisy genome sequences using position-annotated colored de-Bruijn graphs.

Background: Identifying the locations of gene breakpoints between species of different taxonomic groups can provide useful insights into the underlying evolutionary processes. Given the exact locations of their genes, the breakpoints can be computed without much effort. However, often, existing gene annotations are erroneous, or only nucleotide sequences are available.

Diffusing innovative road safety practice: A social network approach to identifying opinion leading U.S. cities.

Objective: This study sought to identify opinion-leading U.S. cities in the realm of safe transportation systems by surveying road safety professionals and asking them to identify places that served as models for road safety.

PLAC8 Localizes to the Inner Plasma Membrane of Pancreatic Cancer Cells and Regulates Cell Growth and Disease Progression through Critical Cell-Cycle Regulatory Pathways.

Pancreatic ductal adenocarcinoma (PDAC) carries the most dismal prognosis of all solid tumors and is generally strongly resistant to currently available chemo- and/or radiotherapy regimens, including targeted molecular therapies. Therefore, unraveling the molecular mechanisms underlying the aggressive behavior of pancreatic cancer is a necessary prerequisite for the development of novel therapeutic approaches. We previously identified the protein placenta-specific 8 (PLAC8, onzin) in a genome-wide search for target genes associated with pancreatic tumor progression and demonstrated that PLAC8 is strongly ectopically expressed in advanced preneoplastic lesions and invasive human PDAC.

Differentiation of multiple types of pancreatico-biliary tumors by molecular analysis of clinical specimens.

Timely and accurate diagnosis of pancreatic ductal adenocarcinoma (PDAC) is critical in order to provide adequate treatment to patients. However, the clinical signs and symptoms of PDAC are shared by several types of malignant or benign tumors which may be difficult to differentiate from PDAC with conventional diagnostic procedures. Among others, these include ampullary cancers, solid pseudopapillary tumors, and adenocarcinomas of the distant bile duct, as well as inflammatory masses developing in chronic pancreatitis.