Filter
Reset all

Subjects

Content Types

Countries

AID systems

Data access

Data access restrictions

Database access

Database access restrictions

Database licenses

Data licenses

Data upload

Data upload restrictions

Enhanced publication

Institution responsibility type

Institution type

Keywords

Metadata standards

PID systems

Provider types

Quality management

Repository languages

Software

Syndications

Repository types

Versioning

  • * at the end of a keyword allows wildcard searches
  • " quotes can be used for searching phrases
  • + represents an AND search (default)
  • | represents an OR search
  • - represents a NOT operation
  • ( and ) implies priority
  • ~N after a word specifies the desired edit distance (fuzziness)
  • ~N after a phrase specifies the desired slop amount
  • 1 (current)
Found 3 result(s)
---<<< This repository is no longer available. This record is out-dated >>>--- The ONS challenge contains open solubility data, experiments with raw data from different scientists and institutions. It is part of the The Open Notebook Science wiki community, ideally suited for community-wide collaborative research projects involving mathematical modeling and computer simulation work, as it allows researchers to document model development in a step-by-step fashion, then link model prediction to experiments that test the model, and in turn, use feeback from experiments to evolve the model. By making our laboratory notebooks public, the evolutionary process of a model can be followed in its totality by the interested reader. Researchers from laboratories around the world can now follow the progress of our research day-to-day, borrow models at various stages of development, comment or advice on model developments, discuss experiments, ask questions, provide feedback, or otherwise contribute to the progress of science in any manner possible.
The Integrated Resource for Reproducibility in Macromolecular Crystallography includes a repository system and website designed to make the raw data of protein crystallography more widely available. Our focus is on identifying, cataloging and providing the metadata related to datasets, which could be used to reprocess the original diffraction data. The intent behind this project is to make the resulting three dimensional structures more reproducible and easier to modify and improve as processing methods advance.