CKBiology: An Active Learning Curriculum Design for Secondary Biology

This research paper presents the design of an active learning curriculum and corresponding software environment called CKBiology, reporting on its implementation in two sections of a Grade 12 Biology course across three design cycles. Guided by a theoretical framework called Knowledge Community and Inquiry (KCI), we employed a design-based research methodology in which we worked closely with a high school biology teacher and team of technology developers to co-design, build, test, implement, and revise this curriculum within a blended learning context. We first present the results of a needs assessment and baseline analysis in which we identify the design constraints and challenges associated with infusing a “traditional” Grade 12 Biology course with a KCI curriculum. Next, we present the design narrative for CKBiology in which we respond to these constraints and challenges, detailing the activity sequences, pedagogical aspects, and technology elements used across three design iterations. Finally, we provide a qualitative analysis of student and teacher perspectives on aspects of the design, including activity elements as well as the CKBiology interface. Findings from this analysis are synthesized into design principles which may serve the wider community of active learning researchers and practitioners

A principled approach to the design of collaborative MOOC curricula

MOOCs have the potential to benefit from the large number of very diverse learners that participate in courses, but this requires a principled approach to MOOC curriculum development. Courses need to take into consideration the diversity of learner experience and intentions, and incorporate scripts that both benefit from the large numbers of learners (crowd-sourcing), as well as enabling small-scale intense collaboration. The real challenge is tying together a set of learning activities and the development of a community knowledge base, with the specific curriculum learning goals of the course. This paper offers a pragmatic approach to developing courses, based on the experience of a MOOC for teacher professional development

Contextualizing the co-creation of artefacts within the nested social structure of a collaborative MOOC

MOOCs have traditionally been seen as providing an individual learning experience, however there is an increasing trend towards enabling social learning in MOOCs. To make online learning at scale more social and collaborative, some MOOCs have introduced cohorts. The interaction between a smaller number of learners, within a cohort, facilitates a richer exchange of experiences and ideas as compared to the effect of “drinking from the fire hose” felt in MOOCs without cohorts. Traditionally, these cohorts have been formed randomly. In this paper, we examine the MOOC “Inquiry and Technology for Teachers”, where we formed cohorts based on student demographics relevant to our course design. Furthermore, these cohorts (which we called Special Interest Groups, SIGs) contained a nested social structure of small teams that worked together on co-creating a final artifact. The different social planes (whole course, SIGs, teams, and individuals) were linked together by pedagogical scripts that orchestrated the movement of ideas and artifacts vertically and horizontally. In this contribution, we analyzed the interaction between these social planes to contextualize the co-creation of artefacts

Internal and external scripts in computer-supported collaborative inquiry learning

We investigated how differently structured external scripts interact with learners’ internal scripts concerning individual knowledge acquisition in a Web-based collaborative inquiry learning environment. 90 students from two secondary schools participated. Two versions of an external collaboration script (high vs. low structured) supporting collaborative argumentation were embedded within a Web-based collaborative inquiry learning environment. Students’ internal scripts were classified as either high or low structured, establishing a 2x2-factorial design. Results suggest that the high structured external collaboration script supported the acquisition of domain-general knowledge of all learners regardless of their internal scripts. Learners’ internal scripts influenced the acquisition of domain-specific knowledge. Results are discussed concerning their theoretical relevance and practical implications for Web-based inquiry learning with collaboration scripts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Database resources of the National Center for Biotechnology Information

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, Reference Sequence, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Entrez Probe, GENSAT, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Peptidome, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov