Online GESS: prediction of miRNA-like off-target effects in large-scale RNAi screen data by seed region analysis.
about
RNAi screening comes of age: improved techniques and complementary approachesAn interactive web-based application for Comprehensive Analysis of RNAi-screen DataAccurate transcriptome-wide prediction of microRNA targets and small interfering RNA off-targets with MIRZA-G.Essential role of miR-200c in regulating self-renewal of breast cancer stem cells and their counterparts of mammary epitheliumKnocking down the obstacles to functional genomics data sharing.Guidelines for the optimal design of miRNA-based shRNAs.High-Throughput Small Interfering RNA Screening Identifies Phosphatidylinositol 3-Kinase Class II Alpha as Important for Production of Human Cytomegalovirus VirionsFlyRNAi.org-the database of the Drosophila RNAi screening center and transgenic RNAi project: 2017 updateA Perspective on the Future of High-Throughput RNAi Screening: Will CRISPR Cut Out the Competition or Can RNAi Help Guide the Way?Seed-effect modeling improves the consistency of genome-wide loss-of-function screens and identifies synthetic lethal vulnerabilities in cancer cells.Defining a Cancer Dependency Map.Human Argonaute 2 Is Tethered to Ribosomal RNA through MicroRNA Interactions.MicroRNAs and Periodontal Homeostasis.c-Myc-miR-29c-REV3L signalling pathway drives the acquisition of temozolomide resistance in glioblastoma.A positive readout single transcript reporter for site-specific mRNA cleavage.Evaluation and control of miRNA-like off-target repression for RNA interference.Regulatory functions of trehalose-6-phosphate synthase in the chitin biosynthesis pathway in Tribolium castaneum (Coleoptera: Tenebrionidae) revealed by RNA interference.While it is not deliberate, much of today's biomedical research contains logical and technical flaws, showing a need for corrective action.
P2860
Q28654521-6FDDAC9C-39AC-498E-B830-46E89427C0CEQ31048261-F5A1F1D9-693B-4FCF-BCDC-F728B20BDD8AQ35089095-48F8F898-5C7E-44ED-AF8D-3B8BC68B8D7AQ36089079-7549C864-9341-4C26-B2CD-93183DE9A30AQ36293771-A5AE8370-056C-4B0C-9CCB-47B0D57B32CEQ37038732-F82AF88B-B49B-42F6-B83A-564F6FCBF1EEQ37224893-A9D83F5A-E172-43D7-AC1C-30D9618EB3F2Q37557088-857B9530-0606-458A-A2E9-DA1233BF47DAQ38517896-290C6D97-50FB-498E-ADA3-237EB2E5D6F4Q38676328-4218BD2C-3188-4429-A40B-DC0CA7FD0072Q38696195-7B3B45ED-4580-4D04-AD64-FA833D3D717FQ38765057-E6D224F5-5517-44B2-8122-EEEBDAC3660AQ38772841-DCA684E5-8863-4C3D-8003-7D9A9EF0F486Q38829331-25382803-E80C-484E-A296-B300560CA155Q40109711-BF0F17C9-C404-48C0-AA68-7A7A39272CA3Q42777701-2A518672-D555-4CC2-9B6B-7A5E73C81753Q47944186-FD868EA7-A813-42C3-BB1F-A3705481D2FDQ52671014-19A48E22-8793-472B-957F-9E8FF935E232
P2860
Online GESS: prediction of miRNA-like off-target effects in large-scale RNAi screen data by seed region analysis.
description
2014 nî lūn-bûn
@nan
2014 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年学术文章
@wuu
2014年学术文章
@zh-cn
2014年学术文章
@zh-hans
2014年学术文章
@zh-my
2014年学术文章
@zh-sg
2014年學術文章
@yue
name
Online GESS: prediction of miR ...... data by seed region analysis.
@ast
Online GESS: prediction of miR ...... data by seed region analysis.
@en
type
label
Online GESS: prediction of miR ...... data by seed region analysis.
@ast
Online GESS: prediction of miR ...... data by seed region analysis.
@en
prefLabel
Online GESS: prediction of miR ...... data by seed region analysis.
@ast
Online GESS: prediction of miR ...... data by seed region analysis.
@en
P2093
P2860
P356
P1433
P1476
Online GESS: prediction of miR ...... data by seed region analysis.
@en
P2093
Bahar Yilmazel
Caroline E Shamu
Frederic Sigoillot
Jennifer A Smith
P2860
P2888
P356
10.1186/1471-2105-15-192
P577
2014-06-17T00:00:00Z
P5875
P6179
1004647081