Searching across hundreds of databases

Our searching services are busy right now. Your search will reload in five seconds.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.

Search

Type in a keyword to search

On page 1 showing 1 ~ 2 papers out of 2 papers

An automated Bayesian pipeline for rapid analysis of single-molecule binding data.

  • Carlas S Smith‎ et al.
  • Nature communications‎
  • 2019‎

Single-molecule binding assays enable the study of how molecular machines assemble and function. Current algorithms can identify and locate individual molecules, but require tedious manual validation of each spot. Moreover, no solution for high-throughput analysis of single-molecule binding data exists. Here, we describe an automated pipeline to analyze single-molecule data over a wide range of experimental conditions. In addition, our method enables state estimation on multivariate Gaussian signals. We validate our approach using simulated data, and benchmark the pipeline by measuring the binding properties of the well-studied, DNA-guided DNA endonuclease, TtAgo, an Argonaute protein from the Eubacterium Thermus thermophilus. We also use the pipeline to extend our understanding of TtAgo by measuring the protein's binding kinetics at physiological temperatures and for target DNAs containing multiple, adjacent binding sites.


Long first exons and epigenetic marks distinguish conserved pachytene piRNA clusters from other mammalian genes.

  • Tianxiong Yu‎ et al.
  • Nature communications‎
  • 2021‎

In the male germ cells of placental mammals, 26-30-nt-long PIWI-interacting RNAs (piRNAs) emerge when spermatocytes enter the pachytene phase of meiosis. In mice, pachytene piRNAs derive from ~100 discrete autosomal loci that produce canonical RNA polymerase II transcripts. These piRNA clusters bear 5' caps and 3' poly(A) tails, and often contain introns that are removed before nuclear export and processing into piRNAs. What marks pachytene piRNA clusters to produce piRNAs, and what confines their expression to the germline? We report that an unusually long first exon (≥ 10 kb) or a long, unspliced transcript correlates with germline-specific transcription and piRNA production. Our integrative analysis of transcriptome, piRNA, and epigenome datasets across multiple species reveals that a long first exon is an evolutionarily conserved feature of pachytene piRNA clusters. Furthermore, a highly methylated promoter, often containing a low or intermediate level of CG dinucleotides, correlates with germline expression and somatic silencing of pachytene piRNA clusters. Pachytene piRNA precursor transcripts bind THOC1 and THOC2, THO complex subunits known to promote transcriptional elongation and mRNA nuclear export. Together, these features may explain why the major sources of pachytene piRNA clusters specifically generate these unique small RNAs in the male germline of placental mammals.


  1. SciCrunch.org Resources

    Welcome to the FDI Lab - SciCrunch.org Resources search. From here you can search through a compilation of resources used by FDI Lab - SciCrunch.org and see how data is organized within our community.

  2. Navigation

    You are currently on the Community Resources tab looking through categories and sources that FDI Lab - SciCrunch.org has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.

  3. Logging in and Registering

    If you have an account on FDI Lab - SciCrunch.org then you can log in from here to get additional features in FDI Lab - SciCrunch.org such as Collections, Saved Searches, and managing Resources.

  4. Searching

    Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:

    1. Use quotes around phrases you want to match exactly
    2. You can manually AND and OR terms to change how we search between words
    3. You can add "-" to terms to make sure no results return with that term in them (ex. Cerebellum -CA1)
    4. You can add "+" to terms to require they be in the data
    5. Using autocomplete specifies which branch of our semantics you with to search and can help refine your search
  5. Save Your Search

    You can save any searches you perform for quick access to later from here.

  6. Query Expansion

    We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.

  7. Collections

    If you are logged into FDI Lab - SciCrunch.org you can add data records to your collections to create custom spreadsheets across multiple sources of data.

  8. Facets

    Here are the facets that you can filter your papers by.

  9. Options

    From here we'll present any options for the literature, such as exporting your current results.

  10. Further Questions

    If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.

Publications Per Year

X

Year:

Count: