Molecular Networks
Systems-scale mapping of biological interactions and their role in health and disease.
Inaugural Symposium · Cambridge, MA
New England
Computational
Biology 2026
Join researchers across New England for a two-day, in-person, student-friendly symposium at the frontier of computation and the life sciences.
Abstract submissions closed Mon Aug 31, 2026. Notifications by Fri Sep 4, 2026.
About the Symposium
NECB 2026 brings together the New England computational biology community for two days of keynotes, invited talks, open-problem sessions, selected talks, and posters at Microsoft Research New England.
We are an in-person, locally rooted symposium with a few simple goals: make it easy for researchers across New England universities, hospitals, and institutes to meet each other; create visibility for junior researchers and trainees; and seed new collaborations at the frontier of computation and the life sciences.
Registration is kept intentionally affordable. The top submitted abstracts will be selected for talks, and outstanding posters will be recognized with poster awards.
Focus Areas
Submissions are welcome across all of computational biology. Five intersecting themes we'll spotlight in 2026:
Molecular Function
Computational methods for annotating and predicting gene and protein function.
Protein Design
Structure prediction, inverse folding, and de novo design of proteins.
Spatial & Single-Cell Omics
Methods, models, and applications at the single-cell and spatial transcriptomics frontier.
Agentic AI for Biology
Autonomous agents, reasoning systems, and agent–scientist collaboration for biological discovery.
Program at a Glance
Draft program — subject to change. Final program will be announced closer to the conference.
For the full schedule, keynote and invited speaker bios, and all accepted abstracts, see the program book (PDF).
Day 1 · Thu Oct 1, 2026
- 8:00 AM Registration desk opens
- 8:45–9:00 AM Opening remarks
- 9:00–9:45 AM
Opening keynote
- Marc Vidal · DFCI · HMS
- 9:45–10:45 AM
Selected talks · Single-cell & spatial
Claudia Chu · Broad Institute · Harvard
A111 Spatial transcriptome and whole-genome characterization of single nuclei in human tissuesJingyuan Hu · Harvard T.H. Chan School of Public Health
A093 FlowMap: Geometry-Consistent Embedding of RNA Velocity for Interpretable Cellular TrajectoriesJiayu Su · Broad Institute
A056 Consistent and scalable detection and comparison of spatial patternsKe Xu · Yale University
A145 GeoSinkhorn Flow: Geometry-Aware Flow Matching for Conditional Dynamics in Single-Cell Data Phenoscapes
- 10:45–11:15 AM Coffee break
- 11:15 AM – 12:15 PM
Invited talks
Alex Lu · Microsoft Research
Vermeer: Autoregressive generative modeling of microscopy predicts protein localizationRong Ma · Harvard Chan
Geometry of Cell States: From Embeddings to DynamicsSamantha Petti · Tufts
Modeling, interpreting, and optimizing high-dimensional genotype-phenotype maps
- 12:15–1:15 PM Lunch
- 1:15–2:15 PM
Selected talks · Protein design & function
Chair: Wengong Jin (Northeastern)
Anna Sappington · MIT CSAIL
A076 Generating proteins with computationally predicted functions and multiple states via multimodal diffusionKerr Ding · Georgia Institute of Technology
A126 Deconvolving mutation effects on protein stability and function with disentangled protein language modelsIndrek Kalvet · University of Washington
A152 De novo design of hydroxylation enzymesShivam Gandhi · Harvard Medical School
A039 Natural compensatory variation reveals how protein language models represent pathogenic epistasis and their ability to generate druggable targets via compensation
- 2:15–4:15 PM Poster session
- 4:15–5:15 PM
Selected talks · Genomics & regulation
Arush Ramteke · New York University
A079 GlintID: Interpretable Modeling of Combinatorial Regulatory LogicArif Ahmad Rather · Boston Children's Hospital · Harvard Medical School
A088 Kidzoi Enables Cell-Type-Specific Regulatory Variant Effect Prediction in the KidneyJacob Schreiber · UMass Chan Medical School
A035 Cherimoya: Lightweight modeling of genomic modalities enables organism-wide analysesLenore Cowen · Tufts University
A185 PhilharmonicDB: Inferring Functional Modules Across the Tree of Life
- 5:15–6:00 PM
Afternoon keynote
- Sergey Ovchinnikov · MIT
Day 2 · Fri Oct 2, 2026
- 8:00 AM Registration desk opens
- 9:00–10:00 AM
Morning keynote
Caroline Uhler · Broad · MIT
Multimodal Data Integration: From Biomarkers to Mechanisms
- 10:00–10:45 AM
Selected talks · Genomics & immunology
Stephanie P. Hao · Boston University
A034 Learned Immune Architectures of Durable Antibody Responses Across VaccinesMahasweta Bhattacharya · Sanofi Research
A100 From human genetics evidence to therapeutic insights at scale: a calibrated language-model specialist for target discovery in immunologyJessika Baral · Harvard Medical School · Broad Institute
A021 Advancing Peptide-HLA Class I Prediction with Active Learning Frameworks for Improved Cancer Vaccine Design
- 10:45–11:15 AM Coffee break
- 11:15 AM – 12:15 PM
Invited talks
Sahin Naqvi · BCH · HMS
Measuring and modeling transcription factor dosage effects- Armita Nourmohammad · Yale
- Yuri Pritykin · Princeton
- 12:15–1:15 PM Lunch
- 1:15–2:15 PM
Selected talks · Clinical & translational
Asif Khan · Harvard Medical School · Massachusetts General Hospital
A156 Pan-cancer risk assessment with an EHR foundation model that predicts what happens next and whenPayton Bock · Boston University
A105 Tissue-of-origin aging clocks reveal composite aging states across cancersRoss Stewart · Northeastern University
A038 Joint Calibration of Multiple Evidence Sources Improves Clinical Variant Classification over Independent CalibrationJustin Delano · Harvard Medical School
A110 PPI-seq: A Massively Parallel System to Decode Genetic Variant Impacts on Protein Interactions
- 2:15–4:15 PM Poster session
- 4:15–5:15 PM
Selected talks · AI methods & applications
Chair: Smita Krishnaswamy (Yale)
Chen Liu · Yale University
A172 ImageFlowNet forecasts disease progression in longitudinal medical imagesReyna Silveira · Harvard OpenBio Student Research Institute
A148 Beyond single-organ pathology: Mapping a unified toxicogenomic network of heavy metal cardiotoxicity and neurotoxicityYilan Wang · Harvard Medical School
A180 Can AI Agents Design Proteins? Agentic vs. Human-Directed De Novo Minibinder Design for a KRAS NeoantigenElizabeth B. Wood · JURA Bio
A118 Scaling CAR-T Targeting of HLA-presented Intracellular Antigens with AI-Driven Experimentation
- 5:15–6:00 PM
Closing keynote
- Zhiping Weng · UMass Chan
- 6:00–6:15 PM Closing remarks · Poster awards
Speakers
Keynote Speakers
Sergey Ovchinnikov
MIT
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MIT Department of Biology. His research develops deep learning methods for protein structure prediction and design, contributing to widely used tools such as ColabFold and modern approaches to evolutionary protein modeling.
Caroline Uhler
Broad Institute · MIT
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Professor at MIT and Co-Director of the Eric and Wendy Schmidt Center at the Broad Institute. Her research bridges statistics, machine learning, and biology, with a focus on causal inference for gene regulation and single-cell analysis.
Marc Vidal
Dana-Farber Cancer Institute · Harvard Medical School
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Professor of Genetics at Harvard Medical School and Founding Director of the Center for Cancer Systems Biology (CCSB) at Dana-Farber Cancer Institute. His group pioneered systems-scale mapping of the human protein–protein interactome to understand how mutations perturb networks in disease.
Zhiping Weng
UMass Chan Medical School
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Li Weibo Professor of Biomedical Research and founding Chair of the Department of Genomics and Computational Biology at UMass Chan Medical School. Her group develops computational methods for functional annotation of the human genome and leads the data analysis center of the ENCODE Consortium.
Invited Speakers
Alex Lu
Microsoft Research New England
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Senior Researcher at Microsoft Research New England. His work explores how machine learning — particularly self-supervised methods — can extract new biological insights from cellular imaging and molecular data.
Sahin Naqvi
Boston Children's Hospital · Harvard Medical School
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Assistant Professor in the Division of Gastroenterology at Boston Children's Hospital and the Department of Pediatrics at Harvard Medical School. His lab uses quantitative approaches to study transcription factor function and developmental gene regulatory programs.
Armita Nourmohammad
Yale University
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Yale University, working at the interface of physics, evolution, and immunology. Her group develops theoretical and computational models of how immune repertoires adapt in response to pathogens and disease.
Samantha Petti
Tufts University
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Assistant Professor of Mathematics and Computer Science at Tufts University. Her group designs mathematical and computational methods to infer fitness landscapes and describe evolutionary processes, with applications to protein sequence and structure analysis.
Yuri Pritykin
Princeton University
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Princeton University, in the Department of Computer Science and the Lewis-Sigler Institute for Integrative Genomics. His group develops computational methods for single-cell and spatial genomics to study immune cell function in cancer and infection.
Rong Ma
Harvard T.H. Chan School of Public Health
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Department of Biostatistics at the Harvard T.H. Chan School of Public Health. She develops statistical methods for high-dimensional inference and dimension reduction, with applications to single-cell genomics and computational biology.
Poster Sessions
Poster sessions run 2:15–4:15 PM on both days. Full abstract text and board numbers will be published in the program book (PDF) closer to the meeting.
Poster format: portrait, up to 36 in wide × 42 in tall (91 × 107 cm). Mounting putty provided on site — please bring your printed poster with you.
Setup: please hang your poster on the assigned board the morning of your session day, before the first talk. Board numbers and full logistics will follow closer to the meeting.
Day 1 · Thu Oct 1, 2026 · 2:15–4:15 PM 87 posters
- A009 Integrating pharmacogenomics and cheminformatics with diverse disease phenotypes for cell type-guided drug discovery Arda Halu · Brigham and Women's Hospital, Harvard Medical School
- A012 Uncovering Heteroxylan Biosynthesis in Rice through Network-Based Gene Discovery and Protein Interaction Analysis Mohsin Ali Nasir · Ohio University
- A015 AI-Guided Therapeutic Strategies to Combat Viral Evolution Muhammad Asif Ali · University of Illinois, Urbana-Champaign
- A020 Luxemia: Pan-Leukemic Algorithmic Relapse Prediction via Federated Gradient Boosting Ensembles with SHAP-Based Clinical Interpretability Jacopo Martelli · Broad Institute
- A025 Deciphering Fetal Endothelial Cell Programs to Enhance Vascular Maturation in Human Organoid Models Paria Pooyan · Royan Institute for stem cell biology and technology
- A027 Modeling the Competition Between Transcription Factors and DNA Repair Enzymes for Recognition of DNA Mismatches Anthony Lau · UMass Chan Medical School
- A028 From Evidence to Simulation: Multi-Agent AI for Cancer Screening Maria Sol Rosito · Dana-Farber Cancer Institute
- A029 Decoding the Thermodynamic Competition Between APP-C99 Dimerization and Membrane Partitioning Sangram Prusty · Boston University
- A030 Collective Dynamics of Confined Water in Amyloid Fibrils Sonali Priyadarshini Nayak · Boston University
- A032 Single-Cell Transcriptomics Reveals a Transient Lipid-Associated Macrophage Response to Beta-Catenin/CBP Inhibition in Oral Squamous Cell Carcinoma Sanjana Bhagavatula · Boston University Chobanian & Avedisian School of Medicine
- A036 Systematic Identification and Characterization of Transcriptional Silencers Across Viral Genomes Mohamed Yousry ElSadec · Bioinformatics Program, Boston University
- A040 A single nucleus multiome QTL atlas of the aging human brain maps regulatory variation underlying Alzheimer's disease risk Louis Liu · Memorial Sloan Kettering Cancer Center, Weill Cornell Medicine
- A041 Signature Recontextualization: Mapping perturbational signatures across biological context Andrew Chen · Boston University
- A042 Understand the Effect of Genetic Variants on Alzheimer's Disease Nguyen Tran · The University of Massachusetts Lowell
- A044 Repeated repurposing of nitrogenase-like proteins revealed by proteome-scale interaction prediction Subhadeep Chowdhury · Bioinformatics program, Faculty of Computing and Data Sciences, Boston University
- A045 Characterization of novel isoforms in whole blood long-read trio RNA sequencing in rare disease Jialan Ma · Broad Institute
- A046 Integrative transcriptomic analysis identifies long noncoding RNA dysregulation and circadian disruption in reward and executive circuits of opioid use disorder Lina Yan · UMass Chan Medical School
- A047 LINGO: A Knowledge Graph-Grounded Foundation Model for Single-Cell Lineage Inference Kaifu Chen · Boston Children's Hospital
- A048 Single-cell transcriptomic profiling of IL-4/IL-13 receptor expression across pancreatic tumorigenesis Stergiani Telliou · Massachusetts General Hospital/ Harvard Medical School
- A049 Externally Validating Steered Disease Features in Single-Cell Foundation Models Mingxin Liu · Department of Biotechnology, Brown University
- A050 Confounder-Aware Feature Correction for Single-Cell Batch Integration Calvin McCarter · Aureka Biotechnologies
- A054 Integrative Radiogenomic Analysis Identifies Imaging-Linked Molecular Subtypes and Biomarkers in Pancreatic Ductal Adenocarcinoma Zhi Qu · Department of Radiation Oncology, University of Rochester Medical Center
- A057 Composable foundations for agentic genomics Nezar Abdennur · UMass Chan Medical School
- A062 The Genomic Interval Query Language (GIQL): A declarative, engine-agnostic grammar for genomic analysis Conrad Bzura · Department of Genomics and Computational Biology, UMass Chan Medical School
- A067 Divide and Conquer: Scalable Partial Correlation Network Inference for High-Dimensional Omics Data Luke Berger · Boston University
- A068 Unsupervised extraction of interpretable, functional programs from spatial transcriptomics through a contrastive learning framework Neal Kewalramani · Boston University
- A069 A Proteogenomic Machine Learning Approach to Evaluate Proteoform-Level Physiological Stability at Genome Scale Senbao Lu · Worcester Polytechnic Institute
- A070 Replicating Pharmacogenomic Associations in All of Us: An EHR-Based Pipeline for FDA-Labeled Drug-Gene Pairs Julia James · University of Massachusetts Lowell
- A071 Interpretable and scalable spatial gene set activity analysis with GESSO uncovers functional tissue architecture Chichun Tan · Department of Biostatistics, Brown University
- A072 Reconstructing Intra-Tumor Fitness Landscapes from scSeq CNA Genotypes via Simulation-Based Bayesian Inference and Deep Learning Maryam KafiKang · University of Connecticut
- A074 CrossHONA: Cross-species HOmologous and Non-homologous gene-aware framework for transcriptomics integration and Annotation Ruohan Wang · Brown University
- A075 scBrieflow: a single-cell analysis platform for understanding morphological readout of optical pooled screens Ege Topkoc · Whitehead Institute
- A078 Sn-seq analysis reveals distinct pathway programs in Gpr149+ vs GPR149- Medium Spiny Neurons in Parkinsons Disease Saatvik Viniak · University of Illinois Chicago
- A081 Benchmarking LLM-based cell type annotation for standardized reanalysis of public single-cell RNA-seq data Eva Fast · Pfizer
- A082 TissueCircuit disentangles active signaling circuits from cell-type structure Taiqi Li · Harvard Medical School
- A083 IGVF Single-cell Perturb-Seq Pipeline, a unified framework for complex data analysis and perturbation inference Lucas Ferreira da Silva · Massachusetts General Hospital · Harvard Medical School
- A085 Stacked SVD or SVD stacked? A Random Matrix Theory perspective on data integration Tavor Baharav · Broad Institute
- A089 Tracing oncogene amplification and genome architecture across single-cell tumor phylogenies Kit Gallagher · Massachusetts General Hospital, Harvard Medical School, Broad Institute
- A090 Identifying Germline Drivers of Neuroblastoma by Their Interaction with Somatic Mutation Jakob Mikhaylov · University of Massachusetts Lowell
- A096 Single-Cell Mapping of Malignant Signaling Networks Guides Drug Combinations Bengi Ruken Yavuz · Cancer Innovation Laboratory, National Cancer Institute
- A099 Folding It In: Structure-Aware Deep Splicing Models Utkarsh Goel · Courant Institute of Mathematical Sciences, New York University
- A101 Transferring Disease Knowledge from Biomedical Literature to Longitudinal Clinical Records for Inborn Error of Immunity Phenotyping Mansooreh Ahmadian · University of Colorado Anschutz Medical Camp
- A112 From Surface to Core: Mechanistic Interpretation of Rare Disease VUSes through Structure-based Analysis Tongxin Wang · Harvard Medical School
- A115 Customizing protein evolution with Fitness Landscape Design (FLD) Vaibhav Mohanty · Harvard University and MIT
- A119 One Age, Many Clocks: System-Specific Metabolomic Aging and Its Links to Diet, Cognition, and Mortality Anastasia Leshchyk · Tufts Medical Center; Tufts University School of Medicine
- A123 DTWarp: Dynamic Time Warping Alignment for RNA and Protein Identifies Protein-Level Effectors of Epithelial-to-Mesenchymal Transition Ruohong Wang · Boston University
- A125 Paired single-cell transcriptome and TCR-repertoire analysis reveals convergent CD4⁺ T cells in recurrent mucosal inflammation Apoorva Sharma · University at Buffalo
- A127 Community Visualization Hub: Integrative Visualization of Multimodal Biomedical Data Across Consortia Vedat Yilmaz · UMass Chan Medical School
- A128 A novel RNA motif discovery pipeline to elucidate GLDR-2 target recognition Melissa Badendieck · Worcester Polytechnic Institute
- A134 ProtScape: A molecular structure and energy-aware representation for protein conformation generation Siddharth Viswanath · Yale University
- A136 Performance of PTM Identification Strategies in Mass Spectrometry Proteomics Search Alec Candib · Bioinformatics Program, Faculty of Computing and Data Science, Boston University
- A137 Evolutionarily constrained immunotherapy targets encoded by oncogene amplicons in cancer Curie Cha · Massachusetts General Hospital, Harvard Medical School, Broad Institute
- A141 Influence Causal Ordering: Scalable Causal Structure from Genome-Scale Perturbation Screens Ritwik Anand · Northeastern University
- A143 Quantitative Modeling of Transcription Factor Binding to UV-Damaged DNA, and Competition with UV-DDB Yuncheng Duan · UMass Chan Medical School
- A144 eIF5A Depletion Increases Ribosome Occupancy at Cotranslational Ssb Chaperone Binding Sites Eimaan Bilal · Stony Brook University
- A150 Resolving Mentions to Ontology Gaps in Biomedical Entity Linking Hyun Seung Lim · Northeastern University
- A151 Generalizable and scalable protein stability prediction with SPURS Ziang Li · Georgia Institute of Technology
- A157 Leveraging naturally occurring sex chromosome variation in humans to identify loci that shape transcriptomic sex differences Erik Owen · MIT / Whitehead Institute
- A158 Incorporating differential geometric features into deep learning models for lung cancer screening Shaun Ng · Boston University Academy
- A159 Visualize Scverse Data Structures and 3D Tissue Maps in Vitessce Mark Keller · Harvard Medical School
- A160 NLP-Driven Identification of Acculturative Barriers to Depression Treatment for Ethnic Minority and Immigrant Youth Tanzila Alam · Harvard Medical School
- A161 Investigating the impact of promoter-promoter interactions on gene regulation Mary Likhite · UMass Chan Medical School
- A164 Integrated analysis of Chromatin Accessibility and Regulon Activity suggests candidate Regulatory Programs in Polarized Porcine Monocyte-derived Macrophages (MDM) Mehak Kapoor · Iowa State University
- A166 Sparse autoencoders recover molecular mechanisms of disease in protein language models Karna Mendonca · Northeastern University
- A167 Interactive Guided Annotation for Single-Cell and Spatial Multi-Omics Visualization in Vitessce Ryan P. Seaman · Harvard Medical School
- A168 HyperFlow: Hypergraph-Based Flow-Matching for Protein Conformation Generation Janmejay Vyas · Northeastern University
- A169 Evaluating Computational Deconvolution Methods and Optimizing Gene Signature Matrices for Rare Cell Detection in Pediatric Cancer Liquid Biopsies Kenia Viri · Salve Regina University
- A170 EMMA: A Generative Energy-based Model for Multiscale Architecture of Spatial Transcriptomics Wonyl Choi · Boston University
- A173 Convergent B-cell receptor sequence features point toward shared antigen targets in colorectal cancer Ping Lu · Massachusetts General Hospital · Harvard Medical School · Broad Institute
- A175 SIMBA+: Interpreting GWAS through single-cell multiomic graphs identifies disease-relevant genes and cell states Junxi Feng · University of California, San Diego
- A176 Reconstructing Early Tumor Evolution in BRCA Carriers Using Long Read Single-Cell RNA-sequencing Grace Li · Krantz Family Center for Cancer Research, Mass General Brigham
- A177 Short tandem repeat polymorphisms mediate transcriptional heterogeneity in Ewing sarcoma Gregory Brunette · Harvard Medical School
- A178 Agentic In Silico Testing of LLM-Generated Biomedical Hypotheses: A CAR-T Biomarker Case Study Yunmai Wang · Computational Biology and Biomedical Informatics, Yale University
- A181 Causal Path Inference on a Literature-Derived Knowledge Graph for Variant Effect Interpretation Jici Jiang · Northeastern University
- A182 In-Silico Characterization of Plumbagin Binding to Multiple Protein Targets Using Molecular Docking Rachel Mathew · South Windsor High School
- A184 CellVELA: Functional Alignment of Cell Foundation Models for Cancer Vulnerability Discovery Jiayi Li · Broad Institute
- A191 Robust dynamics of somatic short tandem repeat expansions using donor-specific assembly Suhas Rao · Harvard Medical School, Department of Biomedical Informatics
- A192 Structural Optimization of Desotamide B for Combating Mycobacterium Tuberculosis Matthew Lin · Independent
- A193 ACCORDION: aligned condition-specific gene representations for multi-sample single-cell analysis Renjie Wu · Massachusetts General Hospital
- A201 Somatic copy number changes of the active and inactive X chromosome are new genomic hallmarks of cancer late-breaking Matthew Leventhal · Dana-Farber Cancer Institute
- A203 Airqtl dissects cell state-specific causal gene regulatory networks with efficient single-cell eQTL mapping late-breaking Matthew Funk · Department of Genomics and Computational Biology, UMass Chan Medical School
- A204 Perturb-LM: Leakage-Aware Language Retrieval of Cell Painting Morphology late-breaking Makenna Rodriguez · National Institutes of Health
- A208 Building dynamical models of multi-step state transitions from single cell gene expression trajectories late-breaking Yukai You · Northeastern University
- A214 Mathematical Modeling of Macrophage Polarization Dynamics and Molecular Feedback to Predict Immune Modulation Strategies late-breaking Veena Naveen · Northeastern University
- A217 Hyaline: Structure and Leakage-Aware Prediction of Kinase Conformational Selectivity late-breaking Manju Selvakumaran · Northeastern University
- A220 Structural Modeling Identifies a Putative, MIF-Independent CD74–IFNGR1 Interface in IFN-γ Signaling late-breaking Nesma E Abdelaal · Brigham and Women’s Hospital, Harvard Medical School
- A221 Integrative in silico analysis of tumor-associated extracellular vesicles reveal markers related to THY-1 in basal-like breast cancer late-breaking Pedro Enrique Soares de Lima · University of Sao Paulo
Day 2 · Fri Oct 2, 2026 · 2:15–4:15 PM 85 posters
- A002 BBB-Nuke: Transport-Aware Prediction of Blood-Brain Barrier Penetration in Small Molecules Noah Abasciano · Attention Labs
- A003 Elucidating enzyme–substrate specificity through co-folding foundation model Xiwei Cheng · Northeastern University
- A007 An Open, Wet-Lab-Free In-Silico Pipeline for Allele-Specific Detection of Autosomal-Dominant Early-Onset Alzheimer's Disease Mutations Sunanditaa Karthikeyan · Northeastern University
- A008 A fast and memory-efficient framework for similarity networks in biology Sean R. Johnson · New England Biolabs
- A010 A Single-Cell Analysis of State-Restricted and Uniform Collateral-Lethality Dependency Signatures in Pancreatic Ductal Adenocarcinoma Om Rajesh · The Woodlands High School
- A011 Elucidating the role of TaVER2 and Rice orthologs in Xylan biosynthesis Samia Nawaz · Ohio University
- A013 Can AI Scientists Discover Better Drugs? Automating Objective Design, Property Prediction, and Molecular Optimization Yikun Zhang · Northeastern University
- A014 Fungal Gene Essentiality Prediction with Genomic Language Models Chen Liao · Dartmouth College
- A018 An ecology-grounded comparison of VAE and diffusion models for microbiome abundances Jeremie Theddy Darmawan · Singapore-MIT Alliance for Research and Technology (SMART)
- A019 Characterizing Ancestry-Related Heterogeneity Between Additive and Recessive GWAS Models for Type 2 Diabetes Christelle Moise · Broad Institute, Broad Summer Scholars Program (BSSP)
- A024 Genetic Regulation of Circular RNAs Reveals a Distinct Molecular Layer Underlying Psychiatric Risk Aarti Jajoo · McLean Hospital
- A026 Embedding kernels for sequence-function relationships Waverly Carabba · Tufts University
- A037 Aging-associated Mechanisms of Aggressiveness in HPV(-) Head and Neck Cancer Lina Kroehling · Boston University
- A043 Single-base mapping of m6A in lncRNAs reveals a distinct landscape linked to transposable elements and RNA processing Euijin Kwon · UMass Chan Medical School
- A052 Structure and Sequence Guided Drug Repurposing Framework for Antimalarial Target Discovery Fatemeh Ensafitakaldani · University of Massachusetts, Boston
- A053 CellFun: Decoding Cellular Functions from Single-Cell and Spatial Transcriptomics with Agentic AI Kulandaisamy Arulsamy · Department of Cardiology, Boston Children's Hospital
- A055 HyperCom: a hypergraph based method to infer cell-resolved cell-cell communication Justin Moy · Boston University
- A059 Agent-driven annotation and interpretation of morphological signatures in optical pooled screening Ana Karla Cepeda Diaz · Whitehead Institute for Biomedical Research
- A060 Sequence-Conditioned Generation of Genome-Targeting Integrases with a Genomic Foundation Model Tanggis Bohnuud · Basecamp Research
- A061 An XOR-based framework for detecting mutually exclusive gene modules in single-cell data Irzam Sarfraz · Boston University Chobanian & Avedisian School of Medicine (CAMED)
- A063 BaseEvolve: AI-guided directed evolution of large serine recombinases for therapeutic gene insertion Aaron Kollasch · Basecamp Research
- A065 Discovering Biological Signals in the Noise Sophia K. Cheng · University of Michigan
- A066 Comprehensive cancer transcriptome analysis reveals lncRNA-derived gene fusions as a widespread class of recurrent alterations with oncogenic potential Chan Zhou · UMass Chan Medical School
- A073 PerturbRx: Treatment-Conditioned Latent Transitions for Patient Drug Response Prediction Yoshitaka Inoue · University of Minnesota
- A077 Statistical detection of drivers of hematopoietic differentiation from lentiviral integration site datasets Giacomo Ceoldo · Boston Children's Hospital - Harvard Medical School
- A084 SigRepo: A Platform For Storing, Sharing, and Comparing Signatures Cameron Vicnaire · Monti Lab, Boston University
- A086 MUTARA: MUTagenesis Analysis of Relative binding Affinity Shogan Sugumar Swamy · Boston Children's Hospital
- A091 Clinico-genomic features predict distinct metastatic phenotypes in cutaneous melanoma Tyler Aprati · Dana-Farber Cancer Institute
- A092 Motif reuse across zinc finger proteins: Insights into function and evolution Lyah Esplana · Department of Chemistry and Biochemistry, Worcester Polytechnic Institute
- A094 Bridging Genome-Scale Metabolism and Adaptive Ecology: A Hybrid Consumer-Resource Framework for Dynamic Microbial Growth Edwin Moses Appiah · University of Connecticut Health Center
- A095 MESH-HR: Multimodal Histopathology and Somatic Genomics for Continuous Breast Cancer Receptor Phenotyping Shaye Carver · Harvard Medical School
- A098 RegScan: A Statistical Framework for Identifying Functional Transcription Factor Binding Sites from Per-Nucleotide Importance Scores Zain M. Patel · Mass General Hospital, Harvard Medical School, Broad Institute
- A102 Learning Sparse Gaussian Graphical Models from Correlated Data Zeyuan Song · Tufts Medical Center · Tufts University
- A103 Developmentally Informed AlphaGenome Modeling to Prioritize Noncoding Variants in Genetically Unresolved Congenital Heart Disease Kristine Yang · Harvard Medical School · Boston Children's Hospital
- A106 Enhancing causal network-based perturbation inference through literature-derived knowledge Zheng Liu · Northeastern University
- A107 REPEL - Random Embedding Perturbation for Enhanced Learning of Protein Function Di Zhou · Tufts University
- A108 Fine-tuning Boltz-1 for protein-protein interaction prediction with positive and negative data Ruqi Liao · Broad Institute · MIT
- A109 Investigating the Transcriptional Program of ACKR1+ Venous Endothelial Cells in Pulmonary Fibrosis Using Single-Cell RNA-sequencing Uyen Chu · Boston University Chobanian and Avedisian School of Medicine
- A113 A Novel ILP Framework to Identify Compensatory Pathways in Genetic Interaction Networks with GIDEON Jocelyn Garcia · Tufts University
- A114 TANGO: High-Throughput, Highly Sensitive Measurements of dCas9 Binding to On- and Off-Target Sequences Michael Tian · University of Massachusetts Medical School
- A116 Discovering disease trajectories using genetic similarity Sujiyanto · University of Massachusetts Lowell
- A120 Mining protein–RNA complexes for recurring RNA-binding motifs Sharra MN Lewis · Worcester Polytechnic Institute
- A121 An Agentic Workflow for Adaptive and Auditable Single-Cell RNA-seq Analysis Luc Francis · Independent Researcher
- A122 Use of Computed Electrostatic and Geometric Information to Investigate Protein Functions and Functional Sites Tina Harati & Mary Jo Ondrechen · Northeastern University and The University of Illinois Chicago
- A124 Genome-Scale Sub-Megabase Chromatin Tracing with DNA-MERFISH Peter Ren · Xiaowei Zhuang Lab, Harvard University
- A129 Applications of AI to biomolecules for both answers and insight into enzyme function Mary Jo Ondrechen · Northeastern University
- A130 A necrosis-associated repeat-element program in metastatic colorectal cancer, and an open problem in separating DNA from RNA Chenyue Lu · Harvard-MIT Health Sciences and Technology · Dana-Farber Cancer Institute
- A131 Understanding and Correcting Representation-Specific Failure Modes in SE(3) Flow-Matching Protein Backbone Generation Michael Widener · Northeastern University / Boston College
- A132 A Spatial Multi-Omics Framework Linking Tumor Cell Composition, Niche Architecture, and Regulatory Drivers in the Tumor Microenvironment Rima Zinjuwadia · White Collar Technologies Inc
- A133 Identifying pathogenic tandem repeat expansions at novel loci in short-read and long-read rare disease datasets Ben Weisburd · Broad Institute
- A135 Beyond Sex Chromosomes: Sex Differences in Transcriptional Signatures of Aged Brain and Alzheimer’s Disease Danielle Firer · MIT
- A139 Mapping Cis-Regulatory Programs of Pancreatic β Cells in Health and Diabetes Maxwell Cmpbell · UMass Chan
- A140 POLARIS: concordance-aware joint analysis of cells and features in single-cell multiomic data Ziqi Fu · Harvard University, Department of Biostatistics
- A142 Consistent Reeb Graph Estimation for Unsupervised Cell-State Topology Discovery Andrew Steindl · Yale
- A146 Comparative Analysis of ZRS–SHH Genomic Architecture Across Vertebrates Ziyan Rao · Department of Genomics and Computational Biology, UMass Chan Medical School
- A147 Interactional experimental design for the efficient demonstration of the Plasmodium inhibitory property of an endosymbiont Eα alone or in association in Anopheles mosquitoes within a context of endosymbiotic diversity for the success of biological control Richard Bationo · Institute of Health Science Research
- A149 SwissIsoform: A Biological and Functional Annotation Database for Translation Start Site Protein Isoforms Anson Ting · Whitehead Institute, UCLA
- A153 Tryptophan Transporters Modulated by Diet Predict Cognitive and Physical Phenotypes: Implications for Precision Nutrition Hannah Lords · Bioinformatics Program, Boston University
- A154 A Bayesian approach to dose-response modeling in sparse data regimes Sameer Rawat · Northeastern University
- A155 Multimodal data-driven approaches for discovery and validation of pneumonia sub-phenotypes Amulya Shastry · Boston University
- A162 Evolutionary Remodeling of the Human Immune Regulatory Genome Nicole Shedd · University of Massachusetts Chan Medical School
- A165 MiLaSol: Modeling Protein Solubility by Mixing Up Multiple Protein Language Models Weiwei Lou · Tufts University
- A171 Bridging Time-to-Event and Generative Deep Learning for Longitudinal Cardiovascular Digital Twins Siying (Avon) Yang · Department of Epidemiology & Biostatistics , Harvard T.H. Chan School of Public Health
- A174 Do Perturbation Models Need to See the Perturbation? Danqi Liao · WindMirror
- A179 Calibrated Computational and Functional Evidence for At-Scale Clinical Classification of In-Frame Indels Haneen Abderrazzaq · Northeastern University
- A183 Differentiable Learning of Nuclear Magnetic Responses with NequIP-NMR Constance Kraay · Harvard University
- A186 Sparse Autoencoders Recover Reproducible Structural Signal in Protein Language Model Latent Space Representations Bridget Liu & Andrew Meng · Columbia University
- A187 Augmenting protein stability predictions from generative models with non-equilibrium thermodynamics and physics-based potentials Kevin Borisiak · Yale University, Department of Physics
- A188 Expression of Cardiac Vagal Sensory Neuron Markers in Human Dilated Cardiomyopathy: A Reanalysis of Public scRNA-seq/snRNA-seq Data Tetsuo Momiy Nakama · Universidad de Ingeniería y Tecnología
- A189 Beyond Proximity: Does AlphaGenome Add Signal Over Splice-Site Annotation in ALS? Arghamitra Talukder · Columbia Univeristy
- A190 An ILP Framework for Repertoire-Scale Antibody Lineage Tracking Faith Abiria Ocitti · Tufts University
- A196 Paired spatial transcriptomics reveals divergent malignant-state and ecosystem remodeling trajectories in recurrent glioblastoma Ali Mohammed Pirani · MD Anderson Cancer Center
- A197 Timing the onset of homologous recombination deficiency before breast cancer diagnosis Michail Andreopoulos · Department of Biomedical Informatics, Harvard Medical School
- A198 OMNIA: Structural Graph Autoencoder Mapping of Microplastic‑Induced Respiratory Gene Regulation late-breaking Sahen Tapar · Lone Star College
- A199 Leveraging Mutational Coldspots to Build an Atlas of Variant Effects late-breaking Mariam Benazouz · University of Washington
- A200 A top-down/bottom-up pipeline for the automatic construction of mechanistic mathematical models: reconstructing the regulatory network of tamoxifen resistance in breast cancer late-breaking Vikas Pandey · The University of Osaka
- A202 LOCALE: Local-Alignment Embeddings for Noise-Robust DNA Search at SRA Scale late-breaking Ryan Synk · University of Maryland
- A205 SIGMA: interface-aware spectral graph learning for metabolic transitions across pathological tissue boundaries late-breaking Bingxue Du · The University of Hong Kong
- A206 AI/ML-enabled screening of FDA-approved drugs against neglected tropic disease targets late-breaking Daniel Korkin · Student at Massachusetts Academy of Math and Science
- A207 Ensemble convergence identifies recurrent structural solutions for pH-responsive CXCL8 antibody design late-breaking Hung-Pin Peng · Clinical Data Center, Office of Data Science, Taipei Medical University, Taipei, Taiwan
- A209 A Computational Framework for Recovering Molecular Relationships from Biological Pathway Diagrams late-breaking Xiwen Zhao · Northeastern University
- A212 Only Two of Ten Nucleic Acid Foundation Models Encode Base-Pairing Partners late-breaking Elliot Tower · University of Edinburgh
- A213 Bayesian Negative Binomial Softmax Regression for Compositional Sequencing Count Data late-breaking Seong-Hwan Jun · University of Rochester
- A215 Selection of oncogenic and CNS-associated programs during breast cancer brain metastasis evolution late-breaking Philipp Hähnel · Mass General Brigham
- A219 Rethinking Large-scale phylogenomics with EukPhylo v.1.0 late-breaking Godwin Ani · UMass Amherst and Smith College
MIT FutureFest Salon
Joint evening event with MIT FutureFest on Day 1 of NECB 2026 — same venue, immediately after the closing keynote.
TopicMind, Body and Soul
Mind, Body and Soul
The Frontiers of Neuroscience, Health, and Artificial Intelligence
What does it mean to understand the human mind, and what happens when that understanding is combined with the full power of artificial intelligence? We have assembled several of the world's leading researchers in AI, medicine, and neuroscience for a salon exploring the frontiers of human biology, health, and machine intelligence. Bringing together scientists, clinicians, technologists, and thinkers from across MIT and Boston's extraordinary research ecosystem, the evening asks how advances in neuroscience, genomics, and AI are converging to transform our understanding of disease, cognition, and what it means to be human.
Featured speakers
Manolis Kellis (MIT) · Smita Krishnaswamy (Yale) · Caroline Uhler (Broad · MIT) · Sergey Ovchinnikov (MIT) · Zhiping Weng (UMass Chan) · Kanaka Rajan (Harvard) · Marinka Zitnik (HMS)
RSVP required →
Please RSVP early — Microsoft Research requires 48 hours notice for building entry and name tags.
Registration
NECB is designed to be accessible. Registration rates are intentionally low to support trainees and researchers across New England. Prices rise gradually as the meeting approaches.
Registration is closed. NECB 2026 has reached capacity.
Add your name to the waitlist to be notified if a spot opens up.
| Category | Early bird By Sep 11, 2026 | Regular By Sep 21, 2026 | Late By Sep 25, 2026 |
|---|---|---|---|
Trainee Students, post-docs, research staff | $50 $105 | $65 $120 | $100 $155 |
Academic Academic, government, media | $150 $300 | $180 $330 | $399 $549 |
Industry | $200 $350 | $230 $380 | $525 $675 |
- All prices in USD. Each column shows ISCB member / non-member.
- No on-site registration.
- Not an ISCB member? Join at iscb.org and register at member rates.
Call for Abstracts
Abstract submissions are now closed. The main round closed Fri Aug 14, 2026 and the late-breaking poster window closed Mon Aug 31, 2026. Thank you to everyone who submitted — author notifications will go out by Fri Sep 4, 2026.
Submission format (for reference)
The main round accepted submissions with two parts, entered through the ISCB submission form:
- A short text abstract of up to 250 words.
- A single-page, print-ready PDF attachment — used directly in the conference abstract book (no copyediting or reformatting will be applied).
The late-breaking window accepted the 250-word text abstract only; late-breaking submissions are for poster presentations only and are not eligible for talks or poster awards.
Print-ready PDF specifications
Page format
- Paper size: US Letter (8.5 × 11 in)
- Maximum length: one page
- Margins: 0.5 in left/right/bottom, 0.75 in top
Title & authors
- Title bold, centered, 14–16 pt
- Authors and affiliations directly below the title
- Mark the presenting author with an asterisk (*)
Body text
- Single column, single-spaced
- Font: 11 pt Times New Roman or similar serif
- Figures, tables, and references OK if within one page
Print-ready
- Submit in final form — no copyediting will be performed
- Authors are responsible for spelling, grammar, and layout
- Ensure figures are of publication quality
Organizers
Affiliations will be added as committee members confirm.
Conference Co-Chairs
Luca Pinello Massachusetts General Hospital · Harvard Medical School · Broad Institute
Predrag (Pedja) Radivojac Northeastern University
Kevin Yang Microsoft Research New England
Steering Committee
- Martha Bulyk · Brigham & Women's Hospital · Harvard Medical School
- Lucy Colwell · Google · University of Cambridge
- Nils Gehlenborg · Harvard Medical School
- Manolis Kellis · MIT
- Smita Krishnaswamy · Yale University
- Xihong Lin · Harvard T.H. Chan School of Public Health
- Donna Slonim · Tufts University
- Olga Vitek · Northeastern University
Organizing Committee
- Ruben Dries · Boston University
- Benjamin Gyori · Northeastern University
- Wengong Jin · Northeastern University
- Dmitry Korkin · Worcester Polytechnic Institute
- Heng Li · Dana-Farber Cancer Institute · Harvard Medical School
- Ying Ma · Brown University
- Jeremy Simon · Dana-Farber Cancer Institute
- Ignacio Vázquez-García · Massachusetts General Hospital · Harvard Medical School · Broad Institute
Coordinators
- Glenda Pay · MGH · HMS
- Diane Kovats · ISCB
Founding Chairs: Luca Pinello & Predrag (Pedja) Radivojac. · Friends of the Conference: Jason Buenrostro.
Abstract Reviewers
With thanks to the trainees volunteering their time to review submissions.
- Ritwik Anand · Northeastern
- Andrew Caruso · AbbVie
- Curie Cha · MGH · HMS · Broad
- Xiwei Cheng · Northeastern
- Kishalay Das · Yale
- Kit Gallagher · MGH · HMS · Broad
- Jocelyn Garcia · Tufts
- Aditya Gorla · UCLA
- Lei Huang · MGH · HMS · Broad
- Benjamin Jones · Yale
- Panos Ketonis · Yale
- Anurendra Kumar · MGH · Stanford
- Senbao Lu · WPI
- Karna Mendonca · Northeastern
- Zain Patel · MGH · HMS · Broad
- Ben Perry · Duke
- Anna Sappington · MIT · HMS
- Kristen Severson · Microsoft
- Ross Stewart · Northeastern
- Siddharth Viswanath · Yale
- Ruohan Wang · Brown
- Will White · Tufts
- Ke Xu · Yale
- Laura Yeoh · BWH · Boston Children's · HMS
- Yikun Zhang · Northeastern
- Nanxiang (Sam) Zhao · Merck
Venue
Microsoft Research New England
One Memorial Drive, Cambridge, MA 02142
- Format: In-person only
- Dates: October 1–2, 2026
The symposium will be held at Microsoft Research New England, in the heart of Kendall Square — a short walk from the MBTA Red Line and easily accessible from across the Boston area and beyond.
Accommodation
We have secured group rates at hotels near the venue for the nights of Sep 30 – Oct 2. Rooms are limited — please book by each hotel's cutoff date.
AC Hotel Cambridge
10 Acorn Park Drive, Cambridge, MA
- From $239/night (Queen/Queen)
- Sleek, European-inspired design
- AC Lounge for evening networking
- Near Alewife (MBTA Red Line)
Holiday Inn Express & Suites Cambridge
250 Monsignor O'Brien Hwy, Cambridge, MA
- From $249/night (King)
- $289/night Double/Double
- Complimentary hot breakfast daily
- Spacious rooms
- Near Lechmere (Green Line) · walking distance to Kendall
Porter Square Hotel
1924 Massachusetts Ave, Cambridge, MA
- From $279/night (Petite Double Twin)
- Up to $330 (Queen Suite)
- Six room types available
- Near Porter Square (MBTA Red Line)
Hotel 1868
1868 Massachusetts Ave, Cambridge, MA
- From $265/night (Mini Queen)
- $285/night Standard Queen
- Near Porter Square (MBTA Red Line)
- Boutique hotel
Sponsors
Sponsorship helps us keep registration affordable, support trainee participation, and recognize outstanding contributions. We welcome partners — academic, industry, and foundations — whose missions align with the symposium.
Interested in sponsoring NECB 2026?
Get in touchKey Dates
| Milestone | Date |
|---|---|
| Registration opens | Mon Jul 6, 2026 |
| Abstract submission opens | Mon Jul 6, 2026 |
| Abstract submission deadline | Fri Aug 14, 2026 · 11:59 PM ET |
| Late-breaking poster submission deadline | Mon Aug 31, 2026 · 11:59 PM ET |
| Author notifications | Fri Sep 4, 2026 |
| Early-bird registration ends | Fri Sep 11, 2026 · 11:59 PM ET |
| Regular registration closes | Mon Sep 21, 2026 · 11:59 PM ET |
| Late registration closes | Fri Sep 25, 2026 · 11:59 PM ET |
| Conference | October 1–2, 2026 |
Note: No on-site registration.
Code of Conduct
NECB follows the ISCB Code of Conduct. We are committed to providing a welcoming and inclusive environment for all participants, and we ask everyone attending or contributing to the symposium to help uphold that standard.
Please report any concerns to the conference chairs or any member of the organizing committee, either in person during the meeting or by email at newenglandcompbio@gmail.com.
Contact
For general inquiries, sponsorship, or speaking interest, please reach the organizing committee at: