Zarkower D et al. (1994) Worm Breeder's Gazette "mab-3 YAC Rescue"

De Bono M, Hodgkin JA, Zarkower D

[Worm Breeder's Gazette, 1994]

mab-3 YAC rescue David Zarkower, Mario de Bono, and Jonathan Hodgkin MRC Laboratory of Molecular Biology, Cambridge, England

Weinkove D (2018) BMC Biol "On microbes, aging and the worm: an interview with David Weinkove."

Weinkove D

[BMC Biol, 2018]

David Weinkove is an associate professor at Durham University, UK, studying host-microbe interactions in the model organism Caenorhabditis elegans. David has been focusing on the way microbes affect the physiology of their hosts, including the process of aging. In this interview, he discusses the questions shaping his research, how they evolved over the years, and his guiding principles for leading a lab.

Miller DM et al. (1992) Worm Breeder's Gazette "unc-4 LacZ Expression in A-Type Motor Neurons"

Miller DM, Niemeyer CJ

[Worm Breeder's Gazette, 1992]

unc-4 LacZ expression in A-type motor neurons David M. Miller and Charles J. Niemeyer, Dept. of Cell Biology, Duke Univ. Medical Ctr, Durham, NC 27710

Grenache DG et al. (1993) Worm Breeder's Gazette "Differential Effects of Dauer-Defective Mutations in L1-Specific Surface Antigen Switching"

Politz SM, Grenache DG

[Worm Breeder's Gazette, 1993]

DIFFERENTIAL EFFECTS OF DAUER-DEFECTIVE MUTATIONS ON L1- SPECIFIC SURFACE ANTIGEN SWITCHING. David G. Grenache and Samuel M. Politz, Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA.

Emmons SW et al. (1994) Worm Breeder's Gazette "Strain Names for non-C. elegans Species."

Emmons SW, Fitch DHA, Leroi AM

[Worm Breeder's Gazette, 1994]

Strain names for non-C. elegans species Scott W. Emmonst, Armand Leroit, and David Fitch, Department of Molecular Genetics, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, NY 10461, Department of Biology, New York University, RmlOO9 Main Bldg., Washington Square, New York, NY 10003

Hall DH et al. (1994) Worm Breeder's Gazette "Cytology of Degenerin-Induced Cell Death in the PVM Neuron"

Driscoll MA, Chalfie M, Gu GQ, Hall DH, Gong L

[Worm Breeder's Gazette, 1994]

Cytology of degenerin-induced cell death in the PVM neuron David H. Hall, Guoqiang Gu+, Lei Gong#, Monica Driscoll#, and Martin Chalfie+, * Dept. Neuroscience, Albert Einstein College of Medicine, Bronx, N.Y. 10461 + Dept. Biological Sciences, Columbia University, New York, N.Y. 10027 # Dept. Molecular Biology and Biochemistry, Rutgers University, Piscataway, N.J. 08855

Amrit FRG et al. (2017) J Vis Exp "Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project."

Ghazi A, Amrit FRG

[J Vis Exp, 2017]

Next generation sequencing (NGS) technologies have revolutionized the nature of biological investigation. Of these, RNA Sequencing (RNA-Seq) has emerged as a powerful tool for gene-expression analysis and transcriptome mapping. However, handling RNA-Seq datasets requires sophisticated computational expertise and poses inherent challenges for biology researchers. This bottleneck has been mitigated by the open access Galaxy project that allows users without bioinformatics skills to analyze RNA-Seq data, and the Database for Annotation, Visualization, and Integrated Discovery (DAVID), a Gene Ontology (GO) term analysis suite that helps derive biological meaning from large data sets. However, for first-time users and bioinformatics' amateurs, self-learning and familiarization with these platforms can be time-consuming and daunting. We describe a straightforward workflow that will help C. elegans researchers to isolate worm RNA, conduct an RNA-Seq experiment and analyze the data using Galaxy and DAVID platforms. This protocol provides stepwise instructions for using the various Galaxy modules for accessing raw NGS data, quality-control checks, alignment, and differential gene expression analysis, guiding the user with parameters at every step to generate a gene list that can be screened for enrichment of gene classes or biological processes using DAVID. Overall, we anticipate that this article will provide information to C. elegans researchers undertaking RNA-Seq experiments for the first time as well as frequent users running a small number of samples.

Naaman Kam et al. (2003) International Worm Meeting "Computer Modeling, Simulation and Analysis of C. elegans Development"

David Harel, Naaman Kam, Michael J Stern, E Jane Albert Hubbard, Amir Pnueli

[International Worm Meeting, 2003]

Vogel G (2002) Science "Neuroscience. Genes keep neurons' house in order."

Vogel G

[Science, 2002]

As any homeowner knows, timely maintenance is vital for keeping a building functioning properly after construction is finished. The same is evidently true for the complex architecture of the nervous system - at least in the roundworm. On page 686, neuroscientists Oliver Hobert, Oscar Aurelio, and David Hall describe a new family of proteins that help keep the wiring of the worm's nervous system tangle free.

Na'aman Kam et al. (2004) East Coast Worm Meeting "COMPUTER MODELING, SIMULATION AND ANALYSIS OF C. elegans VULVAL INDUCTION"

Jasmin Fisher, Amir Pnueli, David Harel, E Jane Albert Hubbard, Na'aman Kam, Michael J Stern

[East Coast Worm Meeting, 2004]

We have been developing a new approach to modeling biological phenomena, focusing on the signaling events that influence vulval fate specification in C. elegans . Our motivation is the striking similarity between the methods and logic of developmental genetics with the languages and tools used in the design of complex computerized systems. Vulval precursor cell (VPC) fate specification is an excellent system to test our approach for two reasons: (1) the mechanisms underlying this process are sufficiently understood to allow meaningful models to be created; and (2) the multiple known inputs that determine fate output create a complexity that can adequately challenge the efficacy of the modeling approach. Developmental genetic data are difficult to make tractable for simulation and analysis by computers ("formalize"), since they are often in a condition-result form in which the precise mechanisms linking the conditions (eg. mutated genes) and the results (eg. phenotypes) are not fully established. We are using two complementary languages, statecharts and live sequence charts (LSCs) , which describe system behaviors using time-constrained logical constructs. Here we present our model of VPC fate specification using the language of LSCs and the Play-Engine tool. The Play-Engine allows data and mechanistic models to be entered by the manipulation of a graphical user interface (GUI) that resembles the pictorial models that biologists draw ( play in ). The GUI also functions as a dynamic pictorial model that depicts computer-executed simulations ( play out ). Using these tools, we have succeeded in representing various types of data commonly obtained in VPC specification experiments, the variability of biological results, cell movement events, and the interdependence of biological behavior and anatomical structure. The model is easily extendable, either by including additional VPC specification data, by linking together GUIs that represent other developmental processes, or by creating links to models in the complementary language of statecharts . The construction and analysis of our model of VPC fate specification has enhanced our understanding of this biological process in several ways. At the simplest level, we have transformed biological data and mechanisms into a database of executable statements of system behavior. Beyond this, however, our modeling has revealed inconsistencies between the "rules" and the actual data in these established papers, and has highlighted interesting gaps in our understanding of this system that we have begun to investigate experimentally.