Author Archives: Combio

Workshop on November 2014

KakaoTalk_workshop2 KakaoTalk_workshop

DigSee was presented at Microsoft Research Asia Faculty Summit 2014.

 

DigSee (Disease gene search engine) was presented at Microsoft Research Asia Faculty Summit 2014, which was held at Beijing, China on October 30-31, 2014 (http://research.microsoft.com/en-us/events/asiafacsum2014/). Find more information about the session ‘computing in Science’ (http://research.microsoft.com/en-US/events/asiafacsum2014/abstracts.aspx) and  DemoFest (http://research.microsoft.com/en-US/events/asiafacsum2014/demofest.aspx).

Jonghyun Han and Hyunju Lee (2015) Adaptive Landmark Recommendations for Travel Planning: Personalizing and Clustering Landmarks using Geo-Tagged Social Media. Pervasive and Mobile Computing. 18:4-17 (IF: 2.079) (COMPUTER SCIENCE, NFORMATION SYSTEMS: 20/139)

Adaptive Landmark Recommendations for Travel Planning: Personalizing and Clustering Landmarks using Geo-Tagged Social Media. Pervasive and Mobile Computing.

  • Author : Jonghyun Han and Hyunju Lee
  • Published Date : 2014
  • Category : Mining in Social Network
  • Place of publication : Pervasive and Mobile Computing

 

Abstract

When travelers plan their trips, landmark recommendation systems considering the properties of their trips will be convenient to help travelers determine locations they will visit. Because interesting content may vary according to travelers and their situations, it is important to recommend personalized landmarks by considering them and their trips. In this paper, we propose an approach that adaptively recommends clusters of landmarks using geo-tagged social media. We first examine the impact of spatial and temporal properties of a trip on the distribution of popular places through large-scale data analysis. Our approach is to compute the significance of landmarks for travelers according to the spatial and temporal properties of their trips. Then, we generate clusters of recommended landmarks, which have similar theme or are contiguous, by utilizing histories of travels’ trajectories. Performances of recommended landmarks by our approach are evaluated against several baseline approaches, showing increased accuracy and satisfaction, compared to the baselines. Through a user study, we also verify that it is applicable to lesser-known places and reflective of local events and seasonal changes. Thus, we expect that the approach is helpful in developing personalized recommendations.

Bayabaatar Amgalan and Hyunju Lee (2014) WMAXC: a weighted maximum clique method for identifying condition-specific sub-network. PLoS One, 2014 Aug 22; 9(8): e104993 (IF: 3.534)

WMAXC: a weighted maximum clique method for identifying condition-specific sub-network.

 

Abstract

Sub-networks can expose complex patterns in an entire bio-molecular network by extracting interactions that depend on temporal or condition-specific contexts. When genes interact with each other during cellular processes, they may form differential co-expression patterns with other genes across different cell states. The identification of condition-specific sub-networks is of great importance in investigating how a living cell adapts to environmental changes. In this work, we propose the weighted MAXimum clique (WMAXC) method to identify a condition-specific sub-network. WMAXC first proposes scoring functions that jointly measure condition-specific changes to both individual genes and gene-gene co-expressions. It then employs a weaker formula of a general maximum clique problem and relates the maximum scored clique of a weighted graph to the optimization of a quadratic objective function under sparsity constraints. We combine a continuous genetic algorithm and a projection procedure to obtain a single optimal sub-network that maximizes the objective function (scoring function) over the standard simplex (sparsity constraints). We applied the WMAXC method to both simulated data and real data sets of ovarian and prostate cancer. Compared with previous methods, WMAXC selected a large fraction of cancer-related genes, which were enriched in cancer-related pathways. The results demonstrated that our method efficiently captured a subset of genes relevant under the investigated condition.

 

‘Bioinformatics Story’ by Prof. Hyunju Lee (Science column, 2014 GIST magazine Vol. 19 No. 1)

GIST소식지2014상반기-Science column 1 GIST소식지2014상반기-Science column 2

Professor Hyunju Lee was invited to Microsoft Research Faculty Summit 2014 to present her text mining research.

facultysummit2014-home-hero

The fifteenth annual Microsoft Research Faculty summit was held on July 14-15, 2014 (http://research.microsoft.com/en-US/events/fs2014/default.aspx).  Leading academic researchers and educators joined Microsoft researchers and engineers to explore future technology trends that will define the twenty-first century (http://research.microsoft.com/en-US/events/fs2014/speakers.aspx).

In the “Science in the Cloud” session at its second day, Professor Hyunju Lee presented her research about “Disease gene search engine (DigSee): Text mining diseae-gene-biological event relationships”. This session illustrates work by academic researchers who have been awarded “Microsoft Azure for Research” cloud awards. Out of the 190 projects awarded, four projects including Prof. Lee’s DigSee project were highlighted (http://research.microsoft.com/en-US/events/fs2014/abstracts.aspx#cloud), and a presentation slide is uploaded (http://research.microsoft.com/en-us/events/fs2014/agenda.aspx). In the “DemoFest”, demo for DigSee was presented (http://research.microsoft.com/en-US/events/fs2014/demonstrations.aspx).

FacultySummit-MS

 

Workshop on January 27th, 2014

사진 1

Ho Jang, Jeongkyun Kim, and Hyunju Lee (2014) Data and Text Mining for Cancer Research. KIISE, 32 (3):61-70 (March 2014).

Data and Text Mining for Cancer Research.

Paper :   link 

Website :   link

Hee-Jin Lee, Tien Cuong Dang, Hyunju Lee, and Jong C. Park (2014) OncoSearch: Cancer Gene Search Engine with Literature Evidence Nucleic Acids Research (9 May 2014) (IF: 8.278).

OncoSearch: Cancer Gene Search Engine with Literature Evidence  Nucleic Acids Research.

  • Author : Heejin Lee, Tien Cuong Dang, Hyunju Lee, and Jong C. Park
  • Published Date : 2014
  • Category : Bioinformatics and Text Mining 
  • Place of publication : Nucleic acids research

 

Abstract

In order to identify genes that are involved in oncogenesis and to understand how such genes affect cancers, abnormal gene expressions in cancers are actively studied. For an efficient access to the results of such studies that are reported in biomedical literature, the relevant information is accumulated via text-mining tools and made available through the Web. However, current Web tools are not yet tailored enough to allow queries that specify how a cancer changes along with the change in gene expression level, which is an important piece of information to understand an involved gene’s role in cancer progression or regression. OncoSearch is a Web-based engine that searches Medline abstracts for sentences that mention gene expression changes in cancers, with queries that specify (i) whether a gene expression level is up-regulated or down-regulated, (ii) whether a certain type of cancer progresses or regresses along with such gene expression change and (iii) the expected role of the gene in the cancer. OncoSearch is available through http://oncosearch.biopathway.org

Paper :   link 

Website :   link

Media covered :  전자신문 (Electronic Times) (2014. 05. 22) 국제신문 (2014.05. 22)뉴스1 (News1) (2014.05.22)

Social Event on December 30th, 2013

KakaoTalk_05bf4d8ed705ae4d
12월 소셜 이벤트를 위해 아침 일찍 메가박스에 방문하여 영화예매를 하였습니다. (다음부턴 전화예약을 이용하는 것이 좋을 것 같습니다.)

 

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영화 보기 전에 저녁식사로 콩나물해장국을 먹고 난 뒤, 사장님께 단체사진 한 장을 부탁드렸습니다.

 

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메가박스 내에는 관람객이 너무 많아서 부끄러움 많은 우리 연구실 학생들에게는 이 사진이 최선이었던 것 같습니다^0^

 

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영화시작시간이 다 달라서 몇몇 학생들은 오락을 하면서 시간을 보내기도 했습니다.

 

영화가 끝난 후 돌아오는 길에 각자 본 영화에 대한 감상과 후기를 공유하며 이번 12월의 소셜이벤트를 마무리 하였습니다.  2014년에는 이번 소셜이벤트에 부득이하게 참여하지 못한 Bayar와 서지윤 학생을 비롯하여 새로운 신입생들과도 함께하는 더 즐거운 소셜이벤트가 되기를 기대합니다.