pulseTD: RNA life cycle dynamics analysis based on pulse model of 4sU-seq time course sequencing data

The life cycle of intracellular RNA mainly involves transcriptional production, splicing maturation and degradation processes. Their dynamic changes are termed as RNA life cycle dynamics (RLCD). It is still challenging for the accurate and robust identification of RLCD under unknow the functional form of RLCD. By using the pulse model, we developed an R package named pulseTD to identify RLCD by integrating 4sU-seq and RNA-seq data, and it provides flexible functions to capture continuous changes in RCLD rates. More importantly, it also can predict the trend of RNA transcription and expression changes in future time points. The pulseTD shows better accuracy and robustness than some other methods, and it is available on the GitHub repository (https://github.com/bioWzz/pulseTD_0.2.0).

Teaching translation and interpreting courses to students’ lacks and wants: An exploratory case study of prioritizing instructional objectives

Though formulation and prioritization of instructional objectives is an important link in the chain of course design, little research has been done in this regard in the field of translation and interpreting (T&I) education. This paper aims at demonstrating how to prioritize instructional objectives in implementing a consecutive interpreting course by inviting students to voice their wants and lacks. Thirty undergraduates and one instructor contributed to data collection through questionnaires and self-evaluation reports. Results of students’ pre-course wants and lacks helped prioritize the objectives formulated in the course design phase. Their pre-course post-course gains and post-course lacks were used to measure teaching effectiveness of prioritized instruction and learning, direct the design of the subsequent course, and thus achieve coordination and integration between courses in the overall T&I curriculum. The current study may inspire colleagues to become selfreflective researchers by formulating and prioritizing their instructional objectives and to contribute to instructional effectiveness at the course level and promote course sequencing and integration at the program level.

Graduate students' research-based learning experiences in an online Master of Education program

The purpose of this research was to better understand graduate students' learning experiences in a research-intensive, online Master of Education (MEd) program. In alignment with the program goal for graduate scholars of the profession, this course-based program adopted an inquiry-based signature pedagogy grounded in the innovative practice of research-based learning. As part of this study, we explored broader program structures, including the cohort-based model, course sequencing and research ethics approval processes, which situate the research-based learning experiences. Several research questions framed our investigation into the experiences of online students who are engaged in a research-active MEd program. Analysis of survey and focus group information contributes to this mixed-methods case study and provides insights into implications for research-based learning in online course-based graduate programs.

Impulse model-based differential expression analysis of time course sequencing data

The global gene expression trajectories of cellular systems in response to developmental or environmental stimuli often follow the prototypic single-pulse or state-transition patterns which can be modeled with the impulse model. Here we combine the continuous impulse expression model with a sequencing data noise model in ImpulseDE2, a differential expression algorithm for time course sequencing experiments such as RNA-seq, ATAC-seq and ChIP-seq. We show that ImpulseDE2 outperforms currently used differential expression algorithms on data sets with sufficiently many sampled time points. ImpulseDE2 is capable of differentiating between transiently and monotonously changing expression trajectories. This classification separates genes which are responsible for the initial and final cell state phenotypes from genes which drive or are driven by the cell state transition and identifies down-regulation of oxidative-phosphorylation as a molecular signature which can drive human embryonic stem cell differentiation.