Search for: All records

Commitment is a multi-dimensional construct that has been extensively researched in the context of organizations. Organizational and professional commitment have been positively associated with technical performance, client service, attention to detail, and degree of involvement with one’s job. However, there is a relative dearth of research in terms of team commitment, especially in educational settings. Teamwork is considered a 21stcentury skill and higher education institutions are focusing on helping students to develop teamwork skills by applied projects in the coursework. But studies have demonstrated that creating a team is not enough to help students build teamwork skills. Literature supports the use of team contracts to bolster commitment, among team members. However, the relationship between team contracts and team commitment has not been formally operationalized.This research category study presents a mixed-methods approach towards characterizing and operationalizing team commitment exhibited by students enrolled in a sophomore-level systems analysis and design course by analyzing team contracts and team retrospective reflections. The course covers concepts pertaining to information systems development and includes a semester-long team project where the students work together in four or five member teams to develop the project deliverables. The students have prior software development experiences through an introductory systems development course as well as multiple programming courses. The data for this study was collected through the team contracts signed by students belonging to one of the 23 teams of this course. The study aims to answer the following research question: How can team commitment be characterized in a sophomore-level system analysis and design course among the student teams?A rubric was developed to quantify the team commitment levels of students based on their responses on the team contracts. Students were classified as high or low commitment based on the rubric scores. The emergent themes of high and low commitment teams were also presented. The results indicated that the high commitment teams were focused on setting goals, effective communication, and having mechanisms in place for timely feedback and improvement. On the other hand, low commitment teams did not articulate the goals of the project, they demonstrated a lack of dedication for attending team meetings regularly, working as a team, and had a lack of proper coordination while working together. 

Information technology professionals are required to possess both technical and professional skills while functioning in teams. Higher education institutions are promoting teamwork by engaging students in cooperative and project-based learning environments. We characterized teams based on their collective orientations and evaluated their team performance in a cooperative project-based learning environment situated in a sophomore-level systems analysis and design course. We explored the orientation patterns in terms of goals, roles, processes, and interpersonal relations (GRPI). Specifically, we analyzed team retrospectives of 23 teams using a mixed-method approach. Findings characterized teams into balanced and unbalanced orientations. Teams with balanced orientations demonstrated a higher level of team performance in terms of academic achievement than the unbalanced category. 

The iron-containing heterodimeric MbnBC enzyme complex plays a central role in the biosynthesis of methanobactins (Mbns), ribosomally synthesized, posttranslationally modified natural products that bind copper with high affinity. MbnBC catalyzes a four-electron oxidation of a cysteine residue in its precursor-peptide substrate, MbnA, to an oxazolone ring and an adjacent thioamide group. Initial studies of MbnBC indicated the presence of both diiron and triiron species, complicating identification of the catalytically active species. Here, we present evidence through activity assays combined with electron paramagnetic resonance (EPR) and Mössbauer spectroscopic analysis that the active species is a mixed-valent, antiferromagnetically coupled Fe(II)Fe(III) center. Consistent with this assignment, heterologous expression of the MbnBC complex in culture medium containing less iron yielded purified protein with less bound iron but greater activity in vitro. The maximally activated MbnBC prepared in this manner could modify both cysteine residues in MbnA, in contrast to prior findings that only the first cysteine could be processed. Site-directed mutagenesis and multiple crystal structures clearly identify the two essential Fe ions in the active cluster as well as the location of the previously detected third Fe site. Moreover, structural modeling indicates a role for MbnC in recognition of the MbnA leader peptide. These results add a biosynthetic oxidative rearrangement reaction to the repertoire of nonheme diiron enzymes and provide a foundation for elucidating the MbnBC mechanism. 

Abstract PANTHER (Protein Analysis Through Evolutionary Relationships, http://www.pantherdb.org) is a resource for the evolutionary and functional classification of protein-coding genes from all domains of life. The evolutionary classification is based on a library of over 15,000 phylogenetic trees, and the functional classifications include Gene Ontology terms and pathways. Here, we analyze the current coverage of genes from genomes in different taxonomic groups, so that users can better understand what to expect when analyzing a gene list using PANTHER tools. We also describe extensive improvements to PANTHER made in the past two years. The PANTHER Protein Class ontology has been completely refactored, and 6101 PANTHER families have been manually assigned to a Protein Class, providing a high level classification of protein families and their genes. Users can access the TreeGrafter tool to add their own protein sequences to the reference phylogenetic trees in PANTHER, to infer evolutionary context as well as fine-grained annotations. We have added human enhancer-gene links that associate non-coding regions with the annotated human genes in PANTHER. We have also expanded the available services for programmatic access to PANTHER tools and data via application programming interfaces (APIs). Other improvements include additional plant genomes and an updated PANTHER GO-slim. 

Abstract The InterPro database (https://www.ebi.ac.uk/interpro/) provides an integrative classification of protein sequences into families, and identifies functionally important domains and conserved sites. Here, we report recent developments with InterPro (version 90.0) and its associated software, including updates to data content and to the website. These developments extend and enrich the information provided by InterPro, and provide a more user friendly access to the data. Additionally, we have worked on adding Pfam website features to the InterPro website, as the Pfam website will be retired in late 2022. We also show that InterPro's sequence coverage has kept pace with the growth of UniProtKB. Moreover, we report the development of a card game as a method of engaging the non-scientific community. Finally, we discuss the benefits and challenges brought by the use of artificial intelligence for protein structure prediction. 

Abstract The Orthology Benchmark Service (https://orthology.benchmarkservice.org) is the gold standard for orthology inference evaluation, supported and maintained by the Quest for Orthologs consortium. It is an essential resource to compare existing and new methods of orthology inference (the bedrock for many comparative genomics and phylogenetic analysis) over a standard dataset and through common procedures. The Quest for Orthologs Consortium is dedicated to maintaining the resource up to date, through regular updates of the Reference Proteomes and increasingly accessible data through the OpenEBench platform. For this update, we have added a new benchmark based on curated orthology assertion from the Vertebrate Gene Nomenclature Committee, and provided an example meta-analysis of the public predictions present on the platform.