Literature DB >> 32106014

We aren't good at picking candidate genes, and it's slowing us down.

Ivan Baxter1.   

Abstract

In order to gain a molecular understanding of the genetic basis for plant traits, we need to be able to identify the underlying gene and the causal allele for genetic loci. This process usually involves a step where a researcher selects likely candidate genes from a list. The process of picking candidate genes is inherently prone to distortion due to human bias, and this is slowing down our research enterprise.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Year:  2020        PMID: 32106014     DOI: 10.1016/j.pbi.2020.01.006

Source DB:  PubMed          Journal:  Curr Opin Plant Biol        ISSN: 1369-5266            Impact factor:   7.834


  7 in total

1.  Fruit Fly Larval Survival in Picked and Unpicked Tomato Fruit of Differing Ripeness and Associated Gene Expression Patterns.

Authors:  Shirin Roohigohar; Anthony R Clarke; Francesca Strutt; Chloé A van der Burg; Peter J Prentis
Journal:  Insects       Date:  2022-05-10       Impact factor: 3.139

2.  Co-expression networks in Chlamydomonas reveal significant rhythmicity in batch cultures and empower gene function discovery.

Authors:  Patrice A Salomé; Sabeeha S Merchant
Journal:  Plant Cell       Date:  2021-05-31       Impact factor: 12.085

3.  Genome-wide association study and gene network analyses reveal potential candidate genes for high night temperature tolerance in rice.

Authors:  Raju Bheemanahalli; Montana Knight; Cherryl Quinones; Colleen J Doherty; S V Krishna Jagadish
Journal:  Sci Rep       Date:  2021-03-24       Impact factor: 4.379

4.  Integration of genome-wide association studies and gene coexpression networks unveils promising soybean resistance genes against five common fungal pathogens.

Authors:  Fabricio Almeida-Silva; Thiago M Venancio
Journal:  Sci Rep       Date:  2021-12-27       Impact factor: 4.379

5.  Genetics as a key to improving crop photosynthesis.

Authors:  Tom P J M Theeuwen; Louise L Logie; Jeremy Harbinson; Mark G M Aarts
Journal:  J Exp Bot       Date:  2022-05-23       Impact factor: 7.298

Review 6.  Capturing Wheat Phenotypes at the Genome Level.

Authors:  Babar Hussain; Bala A Akpınar; Michael Alaux; Ahmed M Algharib; Deepmala Sehgal; Zulfiqar Ali; Gudbjorg I Aradottir; Jacqueline Batley; Arnaud Bellec; Alison R Bentley; Halise B Cagirici; Luigi Cattivelli; Fred Choulet; James Cockram; Francesca Desiderio; Pierre Devaux; Munevver Dogramaci; Gabriel Dorado; Susanne Dreisigacker; David Edwards; Khaoula El-Hassouni; Kellye Eversole; Tzion Fahima; Melania Figueroa; Sergio Gálvez; Kulvinder S Gill; Liubov Govta; Alvina Gul; Goetz Hensel; Pilar Hernandez; Leonardo Abdiel Crespo-Herrera; Amir Ibrahim; Benjamin Kilian; Viktor Korzun; Tamar Krugman; Yinghui Li; Shuyu Liu; Amer F Mahmoud; Alexey Morgounov; Tugdem Muslu; Faiza Naseer; Frank Ordon; Etienne Paux; Dragan Perovic; Gadi V P Reddy; Jochen Christoph Reif; Matthew Reynolds; Rajib Roychowdhury; Jackie Rudd; Taner Z Sen; Sivakumar Sukumaran; Bahar Sogutmaz Ozdemir; Vijay Kumar Tiwari; Naimat Ullah; Turgay Unver; Selami Yazar; Rudi Appels; Hikmet Budak
Journal:  Front Plant Sci       Date:  2022-07-04       Impact factor: 6.627

7.  Using Network-Based Machine Learning to Predict Transcription Factors Involved in Drought Resistance.

Authors:  Chirag Gupta; Venkategowda Ramegowda; Supratim Basu; Andy Pereira
Journal:  Front Genet       Date:  2021-06-24       Impact factor: 4.599

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.