A Mixed-Method Approach to Investigating Difficulty in Data Science Education

The purpose of this study was to define a methodology to identify any disconnect between students and instructors in data science classrooms through analyzing qualitative data. A combined qualitative and quantitative approach was used for analysis of survey data from students, faculty/instructors, and teaching assistants across three institutions. Using a manual content analysis paired with a TF-IDF analysis, researchers were able to pull out frequently used terms within responses and encode them into categories and subcategories. Trends were identified from these categories and subcategories to examine general areas of disconnect within the data science classroom. Additionally, a quality analysis was run to determine the effectiveness of the phrasing of the questions posed during the survey. As a whole, the methods used throughout this research process provide direction for researchers in interpretation and analysis of the survey data in an efficient and time-sensitive manner. Furthermore, it allows researchers to analyze the quality of responses to give insight towards rephrasing of survey questions in future analyses. Although the research was applied to data science classrooms, this method has the potential to be applied into other fields and areas of study when performed with coordination between a field expert and a data scientist

Coenzyme A precursors flow from mother to zygote and from microbiome to host

Coenzyme A (CoA) is essential for metabolism and protein acetylation. Current knowledge holds that each cell obtains CoA exclusively through biosynthesis via the canonical five-step pathway, starting with pantothenate uptake. However, recent studies have suggested the presence of additional CoA-generating mechanisms, indicating a more complex system for CoA homeostasis. Here, we uncovered pathways for CoA generation through inter-organismal flows of CoA precursors. Using traceable compounds and fruit flies with a genetic block in CoA biosynthesis, we demonstrate that progeny survive embryonal and early larval development by obtaining CoA precursors from maternal sources. Later in life, the microbiome can provide the essential CoA building blocks to the host, enabling continuation of normal development. A flow of stable, long-lasting CoA precursors between living organisms is revealed. This indicates the presence of complex strategies to maintain CoA homeostasis

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

A Mixed-Method Approach to Investigating Difficulty in Data Science Education

The purpose of this study was to define a methodology to identify any disconnect between students and instructors in data science classrooms through analyzing qualitative data. A combined qualitative and quantitative approach was used for analysis of survey data from students, faculty/instructors, and teaching assistants across three institutions. Using a manual content analysis paired with a TF-IDF analysis, researchers were able to pull out frequently used terms within responses and encode them into categories and subcategories. Trends were identified from these categories and subcategories to examine general areas of disconnect within the data science classroom. Additionally, a quality analysis was run to determine the effectiveness of the phrasing of the questions posed during the survey. As a whole, the methods used throughout this research process provide direction for researchers in interpretation and analysis of the survey data in an efficient and time-sensitive manner. Furthermore, it allows researchers to analyze the quality of responses to give insight towards rephrasing of survey questions in future analyses. Although the research was applied to data science classrooms, this method has the potential to be applied into other fields and areas of study when performed with coordination between a field expert and a data scientist

Identification of tolerated insertion sites in poliovirus non-structural proteins

Insertion of nucleotide sequences encoding “tags” that can be expressed in specific viral proteins during an infection is a useful strategy for purifying viral proteins and their functional complexes from infected cells and/or for visualizing the dynamics of their subcellular location over time. To identify regions in the poliovirus polyprotein that could potentially accommodate insertion of tags, transposon-mediated insertion mutagenesis was applied to the entire nonstructural protein-coding region of the poliovirus genome, followed by selection of genomes capable of generating infectious, viable viruses. This procedure allowed us to identify at least one site in each viral nonstructural protein, except protein 2C, in which a minimum of five amino acids could be inserted. The distribution of these sites is analyzed from the perspective of their protein structural context and from the perspective of virus evolution