Genes2Networks: Connecting Lists of Proteins by Using Background Literature-based Mammalian Networks

In recent years, in-silico literature-based mammalian protein-protein interaction network datasets have been developed. These datasets contain binary interactions extracted manually from legacy experimental biomedical research literature. Placing lists of genes or proteins identified as significantly changing in multivariate experiments, in the context of background knowledge about binary interactions, can be used to place these genes or proteins in the context of pathways and protein complexes.
Genes2Networks is a software system that integrates the content of ten mammalian literature-based interaction network datasets. Filtering to prune low-confidence interactions was implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from “seed” lists of human Entrez gene names. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is available at http://actin.pharm.mssm.edu/genes2networks.
Genes2Network is a powerful web-based software application tool that can help experimental biologists to interpret high-throughput experimental results used in genomics and proteomics studies where the output of these experiments is a list of significantly changing genes or proteins. The system can be used to find relationships between nodes from the seed list, and predict novel nodes that play a key role in a common function

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

<p>Abstract</p> <p>Background</p> <p>In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP), generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes.</p> <p>Results</p> <p>Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list.</p> <p>Conclusion</p> <p>Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.</p

Infant Spinal Reflex-Testing Apparatus

Final report and team photo for Project 05 of ME450, Fall 2009 semester.Recently-developed equipment can test the presence and stability of spinal-level reflexes in the primary gait muscles of infants 2-10 months old. This baseline data can then assist in the assessment of developmental neuromotor deficits and the development of tailored interventions for infants born with disabilities such as spina bifida, cerebral palsy, and Down syndrome. The goal of this project is to redesign the apparatus used in these tests to be more adjustable and portable.Beverly Ulrich (Kinesiology, U of M)http://deepblue.lib.umich.edu/bitstream/2027.42/86199/1/ME450 Fall2009 Final Report - Project 05 - Infant Spinal Reflex-Testing Apparatus.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/86199/2/ME450 Fall2009 Team Photo - Project 05 - Infant Spinal Reflex-Testing Apparatus.jp

"How Did They Make That?"

Curatorial note from Digital Pedagogy in the Humanities: Miriam Posner offers a modest gallery of various digital projects, virtually disassembling them according to the tools and techniques used in their production. Her goal is to show how each is made so that others might feel empowered to build similar projects or extend the ones highlighted. The Web site is a helpful starting point for students beginning their own digital projects. Students can explore the site and then visit each example project to see how the list of parts and techniques corresponds to and is manifested in specific results. In doing so, they can get a feel for the affordances of different types of digital projects. In addition to the post, Posner also offers a video version of “How Did They Make That?

SNAVI: Desktop application for analysis and visualization of large-scale signaling networks

<p>Abstract</p> <p>Background</p> <p>Studies of cellular signaling indicate that signal transduction pathways combine to form large networks of interactions. Viewing protein-protein and ligand-protein interactions as graphs (networks), where biomolecules are represented as nodes and their interactions are represented as links, is a promising approach for integrating experimental results from different sources to achieve a systematic understanding of the molecular mechanisms driving cell phenotype. The emergence of large-scale signaling networks provides an opportunity for topological statistical analysis while visualization of such networks represents a challenge.</p> <p>Results</p> <p>SNAVI is Windows-based desktop application that implements standard network analysis methods to compute the clustering, connectivity distribution, and detection of network motifs, as well as provides means to visualize networks and network motifs. SNAVI is capable of generating linked web pages from network datasets loaded in text format. SNAVI can also create networks from lists of gene or protein names.</p> <p>Conclusion</p> <p>SNAVI is a useful tool for analyzing, visualizing and sharing cell signaling data. SNAVI is open source free software. The installation may be downloaded from: <url>http://snavi.googlecode.com</url>. The source code can be accessed from: <url>http://snavi.googlecode.com/svn/trunk</url></p

Integrating team science into interdisciplinary graduate education: an exploration of the SESYNC Graduate Pursuit

Complex socio-environmental challenges require interdisciplinary, team-based research capacity. Graduate students are fundamental to building such capacity, yet formal opportunities for graduate students to develop these capacities and skills are uncommon. This paper presents an assessment of the Graduate Pursuit (GP) program, a formal interdisciplinary team science graduate research and training program administered by the National Socio-Environmental Synthesis Center (SESYNC). Quantitative and qualitative assessment of the program’s first cohort revealed that participants became significantly more comfortable with interdisciplinary research and team science approaches, increased their capacity to work across disciplines, and were enabled to produce tangible research outcomes. Qualitative analysis of four themes—(1) discipline, specialization, and shared purpose, (2) interpersonal skills and personality, (3) communication and teamwork, and (4) perceived costs and benefits—encompass participants’ positive and negative experiences and support findings from past assessments. The findings also identify challenges and benefits related to individual personality traits and team personality orientation, the importance of perceiving a sense of autonomy and independence, and the benefit of graduate training programs independent of the university and graduate program environment