Evidence map›Paper›PMID 26286658›Full record

ReviewLearning & memory (Cold Spring Harbor, N.Y.)2015

The need for novel informatics tools for integrating and planning research in molecular and cellular cognition.

Alcino J Silva, Klaus-Robert Müller

Erratum issuedOpen access · diamondAbstract readReview
In one paragraph

Review in Learning & memory (Cold Spring Harbor, N.Y.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Experiment Selection in Meta-Analytic Piecemeal Causal Discovery.IEEE access : practical innovations, open solutions · 2021
    Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 3 countries.

Alcino J SilvaDepartment of Neurobiology, Department of Psychiatry, Department of Psychology, Integrative Center for Learning and Memory, Brain Research Institute, University of California at Los Angeles, Los Angeles, California 90095-1761, USA silvaa@mednet.ucla.edu.
Klaus-Robert MüllerMachine Learning Group, Technische Universität Berlin, 10587, Berlin, Germany Berlin Center for Big Data and Department of Brain and Cognitive Engineering, Korea University, Seoul, 136-701 Korea.
Korea University · KRUniversity of California, Los Angeles · US

Funding

Mechanisms for Neurological Dysfunction in NF1 and Noonan SyndromeR01MH084315 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SILVA, ALCINO J. · 2008 to 2020
$5.0M
NIMH NIH HHS R01 MH084315
6 · The paper itself

Abstract

The sheer volume and complexity of publications in the biological sciences are straining traditional approaches to research planning. Nowhere is this problem more serious than in molecular and cellular cognition, since in this neuroscience field, researchers routinely use approaches and information from a variety of areas in neuroscience and other biology fields. Additionally, the multilevel integration process characteristic of this field involves the establishment of experimental connections between molecular, electrophysiological, behavioral, and even cognitive data. This multidisciplinary integration process requires strategies and approaches that originate in several different fields, which greatly increases the complexity and demands of this process. Although causal assertions, where phenomenon A is thought to contribute or relate to B, are at the center of this integration process and key to research in biology, there are currently no tools to help scientists keep track of the increasingly more complex network of causal connections they use when making research decisions. Here, we propose the development of semiautomated graphical and interactive tools to help neuroscientists and other biologists, including those working in molecular and cellular cognition, to track, map, and weight causal evidence in research papers. There is a great need for a concerted effort by biologists, computer scientists, and funding institutions to develop maps of causal information that would aid in integration of research findings and in experiment planning.

Indexed as

Biomedical ResearchResearch DesignAnimalsCognitionComputational BiologyData CurationNeurosciencesPattern Recognition, AutomatedPublishing

Identifiers

PMID26286658
PMCPMC4561409
OpenAlexW1827087139

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.