Return to home page
Searching: Muskingum library catalog
In response to the COVID-19 outbreak, statewide lending via OhioLINK and SearchOhio has been suspended. OPAL member libraries have closed or are operating at reduced service levels. Please contact your library with specific lending requests or if you need assistance.
Record 47 of 93
  Previous Record Previous Item Next Item Next Record
  Reviews, Summaries, etc...
EBOOK
Conference International Conference on Computational Advances in Bio andmedical Sciences (9th : 2019 : Miami, Fla.)
Title Computational advances in bio and medical sciences [electronic resource] : 9th International Conference, ICCABS 2019, Miami, FL, USA, November 15-17, 2019, Revised Selected Papers / Ion Mandoiu [and more] (eds.).
Imprint Cham : Springer, 2020.

LOCATION CALL # STATUS MESSAGE
 OHIOLINK SPRINGER EBOOKS    ONLINE  
View online
LOCATION CALL # STATUS MESSAGE
 OHIOLINK SPRINGER EBOOKS    ONLINE  
View online
Conference International Conference on Computational Advances in Bio andmedical Sciences (9th : 2019 : Miami, Fla.)
Series Lecture Notes in Computer Science ; 12029
Lecture notes in bioinformatics
LNCS Sublibrary, SL 8, Bioinformatics
Lecture notes in computer science ; 12029.
Lecture notes in computer science. Lecture notes in bioinformatics.
LNCS sublibrary. SL 8, Bioinformatics.
Subject Bioinformatics -- Congresses.
Medical informatics -- Congresses.
Alt Name Mandoiu, Ion.
Murali, T. M.
Narasimhan, Giri.
Rajasekaran, Sanguthevar.
Skums, Pavel.
Zelikovsky, Alexander.
Add Title ICCABS 2019
Description 1 online resource (210 p.).
Note Description based upon print version of record.
Contents Intro -- Preface -- Organization -- Contents -- Detecting De Novo Plasmodesmata Targeting Signals and Identifying PD Targeting Proteins -- 1 Introduction -- 2 Methods -- 2.1 SVM with Dipepetide Features -- 2.2 3-States HMM on JMe -- 2.3 Combination of SVM with HMM -- 3 Results -- 3.1 Datasets -- 3.2 Performance Metrics -- 3.3 Evaluation: SVM Alone -- 3.4 Evaluation: HMM Alone -- 3.5 Evaluation: Combination of SVM and HMM -- 4 Conclusion and Future Work -- References -- The Agility of a Neuron: Phase Shift Between Sinusoidal Current Input and Firing Rate Curve -- 1 Introduction -- 2 Methods
2.1 The Balanced LIF Model -- 2.2 ISI Firing Rate Function for Leaky IAF Model -- 2.3 ISI Firing Rate Function for Balanced LIF Model -- 3 Results and Discussions -- 3.1 The Angle of Phase Shift -- 3.2 The Agility Score of a Neuron -- 4 Conclusion -- References -- Efficient Sequential and Parallel Algorithms for Incremental Record Linkage -- 1 Introduction -- 2 Background -- 3 Methods -- 3.1 Our Approaches -- 3.2 Sequential Algorithms -- 3.3 Parallel Algorithm -- 4 Experimental Environments -- 5 The Datasets -- 6 Results -- 6.1 Results on Real Datasets for Sequential Algorithms
6.2 Results on Real Datasets for Parallel Algorithms -- 7 Conclusions -- References -- Autoencoder Based Methods for Diagnosis of Autism Spectrum Disorder -- 1 Introduction -- 2 Materials and Methods -- 2.1 ABIDE -- 2.2 Data Preprocessing and Brain Networks -- 2.3 Feature Extraction -- 2.4 Feature Extraction -- 2.5 Proposed Autoencoder -- 3 Results and Discussion -- 4 Conclusion -- References -- FastFeatGen: Faster Parallel Feature Extraction from Genome Sequences and Efficient Prediction of DNA N6-Methyladenine Sites -- 1 Introduction -- 2 Methods -- 2.1 Datasets -- 2.2 Feature Engineering
2.3 Machine Learning Algorithms -- 2.4 Feature Selection -- 2.5 Performance Evaluation -- 3 Results and Discussion -- 3.1 Experimental Setup -- 3.2 Parallel Feature Extraction Analysis -- 3.3 Feature Importance Analysis -- 3.4 Performance Analysis -- 3.5 Query Time Analysis -- 4 Conclusions -- References -- Optimized Multiple Fluorescence Based Detection in Single Molecule Synthesis Process Under High Noise Level Environment -- 1 Introduction -- 2 Materials and Models -- 2.1 The Single Molecule Synthesis Process -- 2.2 The Emission Process -- 2.3 The Received Process -- 3 Methods and Algorithms
3.1 Estimation of the Initial Pixel Parameters -- 3.2 Decoding Phase -- 4 Simulations -- 4.1 The Single Molecule Synthesis Process -- 4.2 The Emission Process and the Received Process -- 4.3 Results -- 5 Discussion and Conclusions -- References -- Deep Learning of CTCF-Mediated Chromatin Loops in 3D Genome Organization -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Collection and Preprocessing -- 2.2 DeepCTCFLoop Model Construction -- 2.3 Motif Visualization and Analysis -- 2.4 Model Performance Evaluation -- 3 Results and Discussion
Note 3.1 DeepCTCFLoop Could Accurately Predict Chromatin Loops Formed By Convergent CTCF Motifs
ISBN 9783030461652 (electronic bk.)
3030461653 (electronic bk.)
9783030461645 (print)
OCLC # 1153085953
Additional Format Print version: Mandoiu, Ion Computational Advances in Bio and Medical Sciences : 9th International Conference, ICCABS 2019, Miami, FL, USA, November 15-17, 2019, Revised Selected Papers Cham : Springer International Publishing AG,c2020 9783030461645


If you experience difficulty accessing or navigating this content, please contact the OPAL Support Team