ISSCR 2026Montréal · 8–11 Julycurated for Qichen Huang

Talks & posters worth your time

Filtered from the full program (143 talks, 1,208 posters) against your work — GRN inference, dynamical-systems / physics-informed modeling, spatial transcriptomics, self-organization & morphogenesis, and genetic circuits. Grouped by time so you can build a day plan.

每张卡都标了 相关度评分（对你方向的匹配度）、主题标签，和一句中文关键词，方便快速扫读。每个时间段内按相关度从高到低排。

核心思想把全面的组学数据，喂给以动力学系统为骨架的 physics-informed 模型，去机制性地理解并预测发育中的自组织与形态发生。

数据
时空转录组 · ChIP-seq · RNA-seq · multi-omics

模型
动力学系统（ODE/PDE）× ML，physics-informed，拒绝黑箱

落点
morphogenesis · 自组织 · Waddington landscape · 基因调控网络

66selected sessions

27talks

39posters

23★ don't-miss

Core overlap Strong Adjacent

Nothing matches this filter.

Built from ISSCR 2026 Program & Abstract Book (1,080 pp). Times & rooms transcribed from the printed schedule — double-check against the official app before you walk over, especially poster board numbers (odd boards 4:00–5:15 PM, even boards 5:15–6:30 PM). Notes are one-line reads of each abstract, not the authors' words.
相关度评分（0–100）= 对你研究方向的加权匹配：GRN 建模 · 动力学系统 · Waddington/命运景观 · 生成/物理先验 ML · 自组织与形态发生 · 遗传线路 · 系统生物,以"能否服务于预测细胞命运分化"为准。是我的主观判断,不是官方指标。
Posters that look most "you": W1291 (physics-inspired cell-fate coordinates, UdeM/Mehta) and T1351 (space-filling model of vascular branching, Chao Tang).