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 Date : 2022/11/14 No:298 

Recent News

New Books
Period: 2022-11-14 ~ 2022-11-21
Eco Exhibition:Forest In The Sea
Date: 111.11.01~
Place: Life Science Library, Academia Sinica.(Eco Pavilion)
Time: Mon. ~ Fri. (8:30 ~ 18:00)
Organizers: Life Science Library、Taiwan Environmental Information Association
Awards & Honors
Congratulations to Dr. Yue-ie Hsing of for receiving the ISRFG 2022 Pioneer Award.
Congratulations to Dr. Wen-Harn Pan of IBMS on being elected as the Fellow of the International Union of Nutritional Sciences (IUNS).
Congratulations to Dr. Steve Roffler, Distinguished Research Fellow of IBMS, on receiving the Ministry of Education’s 66th Annual Academic Awards.

Training Courses

【Clinical Trial Lecture-Basic Course】Lesson6-Study design in Phase II clinical trials
Dr.Mey Wang(Academia Sinica Data Science Statistical Cooperation Center)
B1 Auditorium, Institute of Statistical Science

Database Introduction

HSTalks New Releases
HSTalks: The Biomedical & Life Sciences Collection New Releases for November.


11/17 IBC Seminar
Topic:Understand the functional ecology of plant-symbiotic fungi: Challenges and opportunities in non-model systemsbr/> Speaker:Dr. Ko-Hsuan Chen
Date:2022-11-17 11:00 ~ 12:00
Place: IBC R209
11/21 IBMS Seminar
Topic:Discovery of genomic loci of the human cerebral cortex using genetically informed brain atlases.
Speaker:Dr. Chi-Hua Chen
Date:2022-11-21 10:00 ~ 11:00
Place:Webex Only
11/23 IBMS Seminar
Topic:Targeted Protein Modifications: Lessons from PROTACs and PhosTACs.
Speaker:Dr. Po-Han Chen
Date:2022-11-23 14:00 ~ 15:00
Place:B1C Auditorium, IBMS
11/24 IMB Seminar
Topic:Dynamic remodeling of host membranes by self-organizing bacterial effectors
Speaker:Dr. Ting-Sung Hsieh
Date:2022-11-24 11:00 ~ 12:00
Place:IMB B1 Auditorium
11/25 IPMB Seminar
Topic:Shuttle mRNAs beyond the cellular boundary
Speaker:Dr. Tien-Shin Yu
Date:2022-11-25 11:00 ~ 12:00
Place:Auditorium A134 & A133 (Synchronous Broadcasting) Agricultural Technology Building, Academia Sinica
11/28 ICOB Seminar
Topic:MitoTox: a Mitochondrial Toxicity Database and Screening Platform
Speaker:Dr. Chen-Hui Chen
Date:2022-11-28 11:00 ~ 12:00
Place:1F, Auditorium, ICOB


2022 The 14th Shang-Fa Yang Memorial Lecture
11/28 For Taipei
11/30 For Tainan
2022 Antibody Therapeutic Conference (ATC)─Extended Application of Antibody
Time: 2022-11-15(二) 09:00 ~ 17:00
Place: International Convention Hall(Building C), National Biotechnology Research Park.

Important Research

Role of hyperphosphorylation of TDP-43 in the neurodegenerative disease
A research team led by Dr. Yun-Ru (Ruby) Chen at Genomic Research Center, aims to study the misfolded proteins related to neurodegenerative diseases. In 2014, the team reported that there are TDP-43 oligomers in frontotemporal lobar dementia (FTLD) patients and revealed the toxic role of TDP-43 oligomers(Research news: Curbing TDP-43 May Ease the Alzheimer’s Disease Progression) . The follow-up study was done by the team to find that TDP-43 oligomer worsens the pathology in Alzheimer’s disease (AD) model(Research news: Full-length TDP-43 Antibody Confirms Human FTLD). Together, these studies show that TDP-43 oligomers contribute to different neurodegenerative diseases......
soundscape_IR: An open-source toolbox for exploring soundscape diversity
A soundscape is an acoustic landscape formed by sounds of biological, environmental, and anthropogenic sources. With a multitude of acoustic information associated with animal behaviors, environments, and human activities contained in soundscapes, researchers can predict biodiversity change purely by passive listening. However, acoustic analysis remains laborious due to noise interference and the variability of animal vocalizations......
Mechanism and Prediction of Splicing Errors from Human Intronic Mutations
The research teams of Dr. Chien-Ling Lin at the Institute of Molecular Biology, and Dr. Yen-Tsung Huang at the Institute of Statistical Science, Academia Sinica, use massively parallel splicing assay to diagnose and model splicing errors of human intronic mutations. The learned model is highly accurate and facilitates the identification of health-related splicing errors in populations......
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