RSG POSTERS
Poster Session A - Sunday, 5:30 pm - 7:00 pm
Location: Lobby and 105
Poster Session B - Monday, 5:30 pm - 7:00 pm
Location: Lobby and 105
Presenters:
If you are in Session A, you may set up your poster any time between 8:30 am and Noon on Sunday and must remove your poster by 8pm on Sunday. All remaining posters will be discarded.
If you are in Session B, you may set up your poster any time between 8:30 am and Noon on Monday and must remove your poster by 8pm on Monday. All remaining posters will be discarded.
Poster Display Size: - When preparing accepted posters please note that your poster should not exceed the following dimensions: 36 inches wide by 48 inches high. There will be 2 posters per side on the each poster board.
As of November 8, 2017. Subject to change without notice.
| Authors | Title | Board # | Session |
| Richard Chen | Changes in differential expression of genes in normal and metabolically suppressed mice in response to radiation | 1 | A |
| Abdollah Dehzangi, Yosvany López, Sunil Pranit Lal, Ghazaleh Taherzadeh, Abdul Sattar, Tatsuhiko Tsunoda and Alok Sharma | Improving succinylation prediction accuracy by using secondary structure and evolutionary information | 2 | B |
| Kaoru Ohashi, Masashi Fujii, Shinsuke Uda, Hiroyuki Kubota, Hisako Komada, Kazuhiko Sakaguchi, Wataru Ogawa and Shinya Kuroda | Mathematical model analysis for plasma glucose homeostasis regulated by plasma hormones and metabolites in humans | 3 | A |
| Tobias Zehnder, Philipp Benner and Martin Vingron | Enhancer prediction with Hidden Markov Models | 4 | B |
| Oluwafemi Oyamakin and Olalekan Durojaiye | Length and Area Biased distributions on Forest Data using Exponentiated Weibull Distribution | 5 | A |
| Yayoi Natsume-Kitatani, Ken-Ichi Aisaki, Satoshi Kitajima, Samik Ghosh, Hiroaki Kitano, Kenji Mizuguchi and Jun Kanno | Assessment of the effect of valproic acid on organ-specific reactions in mice by analyzing quantitative Percellome toxicogenomics data | 6 | B |
| Merve Cakir, Sayan Mukherjee and Kris Wood | Defining Signaling Networks of Frequently Altered Genes via Label Propagation | 7 | A |
| Emily Johnson, Madeline Frederick, Noel-Marie Plonski, Gail Fraizer and Helen Piontkivska | A novel RNA-Seq analysis pipeline tutorial shows upregulation of ADAR in zika infection and differential VEGFA isoform expression in AML. | 8 | B |
| Alyssa Morrow, Dharmeshkumar Patel, James Kaminski, Bruce Blazar, Nick Haining and Nir Yosef | Maintaining the epigenetic landscape of T stem memory cells from reprogrammed inducible pluripotent stem cells | 9 | A |
| Andre Forbes, Priyanka Dhingra and Ekta Khurana | “Novel computational approach to identify breast cancer drivers using regulatory network rewiring” | 10 | B |
| Duc Do and Serdar Bozdag | Identification of functional MiRNA-Transcription factor-Target gene modules in cancer | 11 | A |
| Yuichi Aoki, Takeshi Obayashi and Kengo Kinoshita | Identification of genomic features in the evolutionary age-specific coexpressed gene modules | 12 | B |
| Jake Lin, Ondrej Cinek, Matti Nykter, Heikki Hyöty, Lenka Kramna, Sami Oikarinen, Riitta Veijola, Jorma Toppari and Mikael Knip | Analysis of the crAssphage sequence in stool samples from children with type 1 diabetes | 13 | A |
| Alexander Martinez-Fundichely and Ekta Khurana | Identifying cancer coding and non-coding drivers involved in somatic structural variations | 14 | B |
| Tomi Häkkinen, Joonas Tuominen, Matti Annala, Kati Kivinummi, Teuvo Tammela, Leena Latonen, Kirsi Granberg, Tapio Visakorpi and Matti Nykter | Chromatin alterations in human prostate cancer | 15 | A |
| Mu Yang, Yi-An Tung, Dung-Chi Wu, Yen-Jen Oyang and Chien-Yu Chen | Incorporating Enhancer-Promoter Interactions in Discovering Regulatory Single Nucleotide Polymorphisms | 16 | B |
| Anastasia Shcherban, Matti Nykter and Juha Kesseli | Integration of multiple track feature detection allows improved sensitivity in identification of transcription factor binding | 18 | B |
| Ameya Kulkarni, Erika Brutsaert, Jessica Mar, Meredith Hawkins, Nir Barzilai and Jill Crandall | Metformin modulates metabolic and non-metabolic pathways in skeletal muscle and subcutaneous adipose tissues of older adults | 19 | A |
| Tomas Rube, Chaitanya Rastogi, Judith Kribelbauer and Harmen Bussemaker | A unified approach for quantifying and interpreting DNA shape readout by transcription factors | 20 | B |
| Xiaojia Tang, Suresh Swaminathan, Karunya K. Kandimalla and Krishna Kalari | Integrative network analysis of insulin time-series response at the blood-brain barrier | 21 | A |
| Felix Yu, Dustin Shigaki and Michael A. Beer | Gkm-SVM Feature Extraction and Summarization | 22 | B |
| Eric Minwei Liu, Alex Martinez Fundichely, Tawny Cuykendall, Jason G. Dumelie, Matthew MacKay, Priyanka Dhingra, Samie R. Jaffrey and Ekta Khurana | Identifying non-coding cancer drivers in CTCF insulators based on recurrence and functional impact analysis | 23 | A |
| Michael Mudgett and Michael A. Beer | Gkm-SVR: Using Support Vector Regression to Train on Continuous Functional Data | 24 | B |
| Anders Wallqvist, Ruifeng Liu and Mohamed Abdulhameed | Molecular Structure-Based Large-Scale Prediction of Chemical-Induced Gene Expression Changes | 26 | B |
| Francesco Vallania, Andrew Tam, Shane Lofgren, Steven Schaffert, Tej Azad, Erika Bongen, Meia Alsup, Michael Alonso, Mark Davis, Ed Engleman and Purvesh Khatri | Leveraging heterogeneity in public data to reduce bias and increase accuracy of cell-mixture deconvolution | 27 | A |
| Gilles Monneret, Pascal Fieth, Alexander Hartmann, Andrea Rau, Florence Jaffrézic and Gregory Nuel | Inferring causal structure in regulatory networks from a mixture of observational and intervention experiments — Laplace approximation, MCMC, and parallel tempering | 28 | B |
| Mariana Martinez Sanchez, Marcia Hiriart and Elena Alvarez-Buylla | The CD4+ T cell regulatory network mediates inflammatory responses during acute hyperinsulinemia: a simulation study | 29 | A |
| Andrew Gentles, Angela Hui, Weiguo Feng, Ramesh Nair, Alice Yu, Majid Shafiq, Erna Forgo, Amanda Khuong, Yue Xu, Chuong Hoang, Matt van de Rijn, Maximilian Diehn and Sylvia Plevritis | Clincally relevant interactions in the NSCLC tumour microenvironment | 30 | B |
| Rahul Metri and Nagasuma Chandra | DMIN : An algorithm for driver mutation identification using influence network and its application in melanoma | 31 | A |
| David Chen, Hollis Wright and Alejandro Lomniczi | Comparative Analysis of ChIP-Seq Peak Calling Methods | 32 | B |
| Liron Yoffe, Avital Gilam, Orly Yaron, Avital Polsky, Luba Farberov, Argyro Syngelaki, Kypros Nicolaides, Moshe Hod and Noam Shomron | Early Detection of Preeclampsia Using Circulating Small non-coding RNA | 33 | A |
| Krishna Praneeth Kilambi, Qifang Xu, Guruharsha Kuthethur Gururaj, Kejie Li, Spyros Artavanis-Tsakonas, Andreas Lehmann and Roland Dunbrack Jr. | Protein domain-based structural interfaces help identify biologically-relevant high-confidence interactions in the human interaction network. | 34 | B |
| Hansaim Lim and Lei Xie | Target gene prediction of transcription factor using a new neighborhood-regularized tri-factorization one-class collaborative filtering algorithm | 35 | A |
| Verena Heinrich, Anna Ramisch and Martin Vingron | Differential analysis of regulation based on epigenetic enhancer prediction | 36 | B |
| Vikrant Palande, Milana frenkel-Morgenstern and Dorith Raviv Shay | Diagnosis of glioma tumors using circulating cell-free DNA | 37 | A |
| Peter Koo, Praveen Anand and Sean Eddy | Improved Predictions of Sequence Specificities of RNA-Binding Proteins by Deep Learning | 38 | B |
| Anat Kreimer, Zhongxia Yan, Nadav Ahituv and Nir Yosef | Meta-analysis of massive parallel reporter assay enables functional regulatory elements prediction | 39 | A |
| Irene Kaplow, Frank Schmitges, Peyton Greenside, Lixia Jiang, Ernest Radovani, Guoqing Zhong, J. Seth Strattan, Daniel Kim, Avanti Shrikumar, Jessika Adrian, Esther Chan, Tejaswini Mishra, Chuan Sheng Foo, Hamed Najafabadi, Hunter Fraser, Jack Greenblatt, Michael Snyder, Timothy Hughes and Anshul Kundaje | An Expanded Understanding of C2H2 Zinc Finger Transcription Factor Binding Preferences | 40 | B |
| Hadas Zur, Rachel Cohen-Kupiec and Tamir Tuller | Tracking and Engineering the Evolution of Organismal Fitness via Multi-Organism mRNA Translation Whole Cell Simulations | 41 | A |
| Yufan Zhou, Diana Gerrard, Junbai Wang, Mahitha Rajendran, Rachel Schiff, Shili Lin, Seth Frietze and Victor Jin | Temporal dynamic reorganization of 3D chromatin architecture in hormone-induced breast cancer and endocrine resistance | 42 | B |
| Davide Chicco, Haixin Sarah Bi, Juri Reimand and Michael M. Hoffman | BEHST: genomic set enrichment analysis enhanced through integration of chromatin long-range interactions | 43 | A |
| Shuonan Chen and Jessica Mar | Developing Bayesian modeling methods to characterize gene regulatory relationships in single cells | 44 | B |
| Suvi Luoto, Juha Kesseli, Matti Nykter and Kirsi Granberg | Computational characterization of suppressive immune microenvironment in glioblastoma | 45 | A |
| Rosanna Smith, Patrick Stumpf, Sonya Ridden, Aaron Sim, Sarah Filippi, Heather Harrington and Ben MacArthur | Nanog Fluctuations in Embryonic Stem Cells Highlight the Problem of Measurement in Cell Biology | 46 | B |
| Elaheh Moradi and Matti Nykter | Supervised pathway level analyses for classification of Alzheimer’s disease | 47 | A |
| She Zhang and Ivet Bahar | Cell-Cell Heterogeneities at the 3D Genome Scale Investigated by the Gaussian Network Model | 48 | B |
| Nan Papili Gao, Thomas Hartmann and Rudiyanto Gunawan | Clustering and lineage inference in single cell transcriptional analysis of cell differentiation | 49 | A |
| Kiley Graim, Chandra Theesfeld, Olga Troyanskaya, Karin Sorenmo and Dima Gorenshteyn | The Genomic Landscape of Canine Mammary Tumors and its Potential as a Translational Model of Human Breast Cancer | 50 | B |
| Lingfei Wang and Tom Michoel | Wisdom of the crowd from dimension reduction outperforms supervised learning | 52 | B |
| Tianbao Li, Qi Liu, Nick Garza and Victor Jin | Integrative analysis reveals a functional and regulatory role of H3K79me2 in mediating alternative splicing in blood cancer cells | 53 | A |
| Takeshi Obayashi, Yuichi Aoki and Kengo Kinoshita | Logit-transformation of the coexpression MR index enables comparative coexpression analyses. | 54 | B |
| Noel-Marie Plonski, Madeline Fredrick, Emily Johnson, Gail Fraizer and Helen Piontkivska | Virtualbox-based RNA-Seq differential expression pipeline using open source tools: from fastq files to presentable results. | 55 | A |
| Hatice Osmanbeyoglu, Petar Jelinic, Douglas Levine and Christina Leslie | Inferring transcriptional regulatory programs in gynecological cancers | 56 | B |
| Narmada Sambaturu and Nagasuma Chandra | Cutting through the complexity of genomic data: A general method to identify candidate genes | 57 | A |
| Luis Santos, Robert Vogel, Jerry Chipuk, Marc Birtwistle, Pablo Meyer and Gustavo Stolovitzky | Cell to cell variability in mitochondrial abundance enables fractional control of apoptosis | 58 | B |
| Evan Paull, Federico Giorgi, Mariano Alvarez and Andrea Califano | Pan-cancer analysis reveals functional interactions between genomic and transcriptional drivers of disease | 59 | A |
| Luca Ponzoni and Ivet Bahar | Structural dynamics is a determinant of the functional significance of missense variants | 60 | B |
| Brian Ross, Fabio Anaclerio and James Costello | Measuring chromosome conformation by fluorescence microscopy | 61 | A |
| Allison Richards, Amanda Muehlbauer, Adnan Alazizi, Camilla Cascardo, Roger Pique-Regi, Ran Blekhman and Francesca Luca | Changes in microbiota composition modify host gene expression | 62 | B |
| Ushma Majmudar and Jessica Mar | Investigating machine learning methods for proteogenomics prediction in cancer biology | 63 | A |
| Jakub Mieczkowski, Brejnev Muhire and Michael Tolstorukov | Regulating the regulators: analysis of the differential expression of histone variant genes in normal development and during carcinogenesis | 65 | A |
| Ariel Afek and Raluca Gordan | Widespread increase in transcription factor-DNA binding due to mismatch damage | 66 | B |
| Slim Fourati and Aarthi Talla | Pathway-level approach to predict symptoms caused by respiratory viral infection | 67 | A |
| Yaron Orenstein, Huy Quoc Nguyen and Polly Fordyce | Reverse de Bruijn sequence to minimize cost and space of peptide arrays | 68 | B |
| Yi-An Tung, June-Tai Wu and Chien-Yu Chen | Integrating multiple cell types to enhance accuracy of predicting cross-cell type enhancer activities by deep learning | 69 | A |
| Vakul Mohanty, Ge Zhang and Kakajan Komurov | Comprehensive analysis of the variability of host organ function in cancer pathogenesis | 70 | B |
| Johnny Israeli, Raunaq Rewari, Irene Kaplow, Robin Fropf, Melanie Weilert, Julia Zeitlinger and Anshul Kundaje | Learning nucleotide-resolution in vivo transcription factor binding footprints and predictive sequence grammars from ChIP-seq and ChIP-nexus data | 71 | A |
| Sridhar Hariharaputran | Construction, visualization and analysis of protein interaction network for Mycobacterium species | 72 | B |
| Daniel Pique, John Greally and Jessica Mar | Identification and Characterization of Novel Oncogene Candidates in Invasive Breast Carcinoma | 73 | A |
| Albert Pla Planas, Xiangfu Zhong, Fatima Heinicke and Simon Rayner | A Deep Learning Approach for miRNA Target Prediction: Exploring the Importance of Pairing Beyond Seed Region | 74 | B |
| Rajiv Movva, Peyton Greenside, Avanti Shrikumar and Anshul Kundaje | Inferring nucleotide-resolution regulatory sequence grammars and non-coding regulatory variants from massively parallel reporter assays | 75 | A |
| Avanti Shrikumar, Peyton Greenside, Johnny Israeli and Anshul Kundaje | Not Just a Black Box: Interpretable Deep Learning for Genomics | 76 | B |
| Judith F Kribelbauer, Namiko Abe, Chaitanya Rastogi, Tomas Rube, Richard S Mann and Harmen J Bussemaker | Disentangling DNA Sequence and Shape Read-Out for a Multi-Protein Hox Complex in vitro and in vivo | 77 | A |
| Aarthi Talla, Joshua Burkhart, Mehrad Mahmoudian, Zafer Aydın and Slim Fourati | Systemic inflammation is the most robust predictor of symptoms following respiratory viral infection | 78 | B |
| Naomi Yamada, Nina Farrell, William K.M. Lai, B. Franklin Pugh and Shaun Mahony | Characterizing protein-DNA binding event subtypes in ChIP-exo data | 79 | A |
| Yuri Pritykin, Yuheng Lu, Steve Lianoglou, Aly Khan, Eric Bo Zheng and Christina Leslie | CLIPanalyze: an algorithm to detect and analyze peaks in CLIP-seq data | 80 | B |
| Robert J. Prill, Robert Vogel, Guillermo Cecchi, Grégoire Altan-Bonnet and Gustavo Stolovitzky | Noise-driven causal inference in biomolecular networks | 81 | A |
| Manu Setty, Vaidotas Kiseliovas, Linas Mazutis and Dana Pe'Er | Palantir characterizes cellular differentiation potential in human hematopoiesis | 82 | B |
| Boxiang Liu, Salil Bhate, Nadine Hussami, Avanti Shrikumar, Tyler Shimko, Scott Longwell, Stephen Montgomery and Anshul Kundaje | A multi-modal neural network model for learning cis and trans regulation of stress response in S. cerevisiae | 83 | A |
| Dinesh Manandhar, Ami Kabadi, Lingyun Song, Jennifer Kwon, Feimei Liu, Lee Edsall, Alexias Safi, Timothy Reddy, Koji Tsumagari, Melanie Ehrlich, Gregory E. Crawford, Charles Gersbach and Raluca Gordan | Genome-wide insights into the efficiency of cellular reprogramming | 84 | B |
| Amin Emad and Saurabh Sinha | Phenotype-relevant transcriptional regulatory networks identify pan-cancer regulatory mechanisms | 85 | A |
| Yuheng Lu, Jing-Ping Hsin, Gabriel Loeb, Christina Leslie and Alexander Rudensky | The effect of cellular context on miR-155 mediated regulation of gene expression in four major immune cell types | 86 | B |
| Aaron Baker and Anthony Gitter | Improving subnetwork identification with pathway simulation | 87 | A |
| Ayush Raman, Haidong Yi, Amy Pohodich, Huda Zoghbi and Zhandong Liu | Detection of confounders and identifying potential hypotheses using genome wide expression datasets | 88 | B |
| Konstantine Tchourine, Christine Vogel and Richard Bonneau | Condition-Specific Modeling of Biophysical Parameters Advances Inference of Regulatory Networks | 89 | A |
| Nicolas Eng and Michael A. Beer | The Spectrum of Transcription Factor Binding Site Disruption Contributing to Human Immune Regulatory Variation | 90 | B |
| Yuchun Guo, Michael Closser, Konstantin Krismer, Hynek Wichterle and David Gifford | High resolution discovery of chromatin interactions reveals regulatory control of distal enhancers during neuronal specification | 91 | A |
| Jin-Woo Oh, Wang Xi, Amy Xiao and Michael A. Beer | Using Gapped-kmer Composition to Detect Conserved Enhancers where Sequence Alignment Fails | 92 | B |
| Huanan Zhang, Catherine Lee, Zhuliu Li, John Garbe, Cindy Eide, Rui Kuang and Jakub Tolar | Multitask Clustering across Multiple Single-cell RNA-seq datasets Identifies Cell Sub-populations and Markers in Recessive Dystrophic Epidermolysis Bullosa | 93 | A |
| Rani Powers and James Costello | Identifying molecular signatures of disease using differential association networks | 94 | B |
| Mark Hickman, Abigail Smith, Andrea Jackson, Amanda Tursi and Julianne Thornton | Gene function is a major determinant of expression level | 95 | A |
| Mo Huang, Jingshu Wang, Eduardo Torre, Hannah Dueck, Sydney Shaffer, Roberto Bonasio, John Murray, Arjun Raj, Mingyao Li and Nancy R. Zhang | SAVER: Gene expression recovery for single cell RNA sequencing | 96 | B |
| Xintong Chen, Sander Houten, Kimaada Allette, Robert Sebra, Gustavo Stolovitzky and Bojan Losic | Characterization of drug-induced splicing complexity in prostate cancer cell line using long read technology | 98 | B |
| Carmen Argmann, Aritz Irizar, Huabao Xiong, Gabriel Hoffman, Aleksandar Stojimirovic, Lauren Peters, Radu Dobrin, Josh Friedman, Rodrigo Mora, Sergio Lira, Eric Schadt and Bojan Losic | Predicting IBD disease progression from time-dependent omics mouse models | 99 | A |
| Rene Welch, Dongjun Chung, Jeffrey Grass, Robert Landick and Sunduz Keles | Data exploration, quality control and statistical analysis of ChIP-exo/nexus experiments | 100 | B |
| Arvind Singh Mer, Ben Brew, Janosch Ortmann, Anna Goldenberg and Benjamin Haibe-Kains | Xeva: an R package for patient derived xenograft data management and analysis | 101 | A |
| Sung-Cheol Kim, Stacey Gifford and Pablo Meyer | Quantitative modeling of spatio-temporal properties of an enzyme cluster | 102 | B |
| Di He, Jiadong Ji and Lei Xie | ENSEMBLE.JDINAC: A New Method for Genome-Scale Context-Specific Network-Based Disease Classification and Biomarker Identification | 103 | A |
| Tolutola Oyetunde and Yinjie Tang | BoostGAPFILL: improving the fidelity of metabolic network reconstructions through integrated constraint and pattern-based methods | 104 | B |
| Chloé Bessiere, Charles Lecellier, Laurent Bréhélin, Sophie Lèbre and May Taha | Probing instructions for expression regulation in gene nucleotide compositions | 105 | A |
| Chun–kyung Lee and Jung–min Yang | Mathematical Modelling of Anoikis Process | 106 | B |
| Mi Yang, Jaak Simm, Yves Moreau, Julio Saez-Rodriguez and Pooya Zakeri | Generating clinically actionable insights from large scale drug screenings with transfer learning | 107 | A |
| Jung Ho Kong, Dong Hyo Kim, Kunyoo Shin and Sanguk Kim | Identification of biomarkers and prediction of survival based on exome sequencing of the mouse model of aggressive bladder cancer | 108 | B |
| Malika Aid, Paul Edlefsen and Rafik Sekaly | HIV integration sites in vivo: Selection for genomic sites, orientation and cellular pathways | 109 | A |
| Bo Zhang | HiCPlus: Resolution Enhancement of Hi-C interaction heatmap | 110 | B |
| Seong Kyu Han and Sanguk Kim | Biological functions rather than individual genes can explain the phenotypic differences observed between human and mouse orthologous genes | 111 | A |
| Daniela Perry and Jeremy Gunawardena | Identification of Non-invasive Cytokine Biomarkers for Polycystic Ovary Syndrome Using Supervised Machine Learning | 112 | B |
| Giacomo Corleone, Darren K Patten and Luca Magnani | Understanding the role of epigenetic reprogramming during the development od endocrine therapy resistance | 113 | A |
| Farahnaz Golestan Hashemi | A Genome Mining Toolbox for CRISPR-associated Cas9 orthologues | 114 | B |
| Adel Ait-Hamlat, Alessandra Carbone, Thierry Jaffredo, Pierre Charbord and Charles Durand | HubNeD, a new Gene Regulatory Network inference method based on hub detection | 115 | A |
| George Rosenberger, Yansheng Liu, Hannes L Röst, Christina Ludwig, Alfonso Buil, Ariel Bensimon, Martin Soste, Tim D Spector, Emmanouil T Dermitzakis, Ben C Collins, Lars Malmström and Ruedi Aebersold | Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS | 116 | B |
| Philipp Drewe-Boss, Hans-Hermann Wessels and Uwe Ohler | A General Approach for Identification of RNA-Protein Interactions and RNA Modifications from CLIP-data | 117 | A |
| Kihyun Lee, Hyunwoo Cho, Zhong-Dong Shi, Christina Leslie and Danwei Huangfu | Integrative genomic analysis of FOXA2-deficient human pluripotent stem cells in pancreatic development | 118 | B |
| Raymund Bueno and Jessica Mar | Exploring the transcriptional activity of the BRCA gene in breast cancers using Bayesian Networks | 119 | A |
| S M Minhaz Ud-Dean, Ioan Filip, Marta Galanti, Ruthie Birger, Devon Comito, Benjamin Lane, Chanel Ligon, Haruka Morita, Sadiat Ibrahim, Eudosie Tagne, Atinuke Shittu, Gregory Freyer, Raul Rabadan, Paul Planet, Peter Dayan and Jeffrey Shaman | Symptomatic identification of respiratory viral infections | 120 | B |
| Ziga Avsec, Mohammadamin Barekatain, Jun Cheng and Julien Gagneur | Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks | 121 | A |
| Yingqian Zhan, Liuyang Cai, Vincent Schulz, Patrick Gallagher, Yijun Ruan and Jeff Chuang | Genome organization at kilobase level revealed signature activities in primary human erythroid cells | 122 | B |
| Fumiko Shimizu and Gabriela Chiosis | Prediction of response to HSP90 inhibitors in cancer cells using gene expression data | 123 | A |
| Marjorie Liebling, Shuonan Chen, Samuel Zimmerman, Daniel Pique and Jessica Mar | Developing Interactive Software to Interrogate Bayesian Networks for Single Cell Transcriptomic Data | 124 | B |
| Kihyun Lee, Hyunwoo Cho, Zhong-Dong Shi, Christina Leslie and Danwei Huangfu | Integrative genomic analysis of FOXA2-deficient human pluripotent stem cells in pancreatic development | 125 | A |
| Sagar Chhangawala, Surajit Dhara, Steven Leach and Christina Leslie | Chromatin accessibility maps of Recurrence in Pancreatic Cancer | 126 | B |
| Lorenzo Calviello and Uwe Ohler | Detecting and quantifying translation on multiple RNA isoforms. | 127 | A |
| Jinyuan Yan, Maxime Deforet, Kerry Boyle, Rayees Rahman, Raymond Liang, Chinweike Okegbe, Lars Dietrich, Weigang Qiu and Joao Xavier | Bow-tie signaling in c-di-GMP: machine learning in a simple biochemical network | 129 | A |
| Jia Wu, Darryl Abbott, Meryem Terzioglu, Dolores Mahmud, Nadim Mahmud, William Miller and Neda Bagheri | Gaussian Mixture Models and Machine Learning Predict Megakaryocytic Growth and Differentiation Potential Ex Vivo | 130 | B |
